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Dissertations / Theses on the topic 'Green Computing'
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Franci, Alessandro. "Green Cloud Computing: una rassegna comparativa." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2010. http://amslaurea.unibo.it/1181/.
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La rapida crescita di Internet e del numero di host connessi sta portando sempre di più alla nascita di nuove forme di tecnlogie ed applicazioni serverside, facendo del client un thin-client. Il Cloud Computing offre una valida piattaforma a queste nuove tecnologie, ma esso si deve confrontare con diverse problematiche, fra cui la richiesta energetica sempre più crescente, che si ripercuote su un'inevitabile
aumento dei gas serra prodotti indirettamente.
In questa tesi analizzeremo i problemi energetici legati al Cloud Computing e le possibili soluzioni, andando infine a creare una tassonomia fra i diversi Cloud Computing più importanti sul mercato attuale.
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Talebi, Mujtaba. "Computer power consumption benchmarking for green computing." Click here for download, 2008. http://proquest.umi.com/pqdweb?did=1490085671&sid=1&Fmt=2&clientId=3260&RQT=309&VName=PQD.
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Bi, Mingsong. "OPTIMIZING PROCESSOR AND MEMORY FOR GREEN COMPUTING." Diss., The University of Arizona, 2011. http://hdl.handle.net/10150/205424.
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Energy efficiency has become one of the most important factors in the development of computer systems. Increasingly power-hungry processors and memory subsystem have reinforced the need for aggressive power management. Dynamic voltage scaling has become a common consideration for designing energy efficient CPUs in systems ranging from portable devices to large-scale systems. As applications become more data centric and put more pressure on memory subsystem, managing energy consumption of main memory is also becoming critical. Subsequently in this dissertation, we address the issues in designing energy efficient CPU and memory for personal computing devices as well as large-scale systems.For large-scale systems, we address memory subsystem dedicated to buffer cache which accounts for the majority of memory usage in server environment. We take advantage of the I/O handling routines in the OS kernel to hide the delay incurred by the memory state transition so that performance degradation is minimized while high energy savings is achieved. We also address interactive workloads, which account for the bulk of the processing demand on modern mobile or desktop systems. We propose Interaction-Aware Dynamic Voltage Scaling (IADVS) for CPU and Interaction-Aware Memory Energy Management (IAMEM) for memory. The IA framework relies on automatic correlation of user-initiated tasks with the demand placed on CPU and memory to accurately predict power states for CPU and memory. Both mechanisms achieve maximal energy savings while minimizing the impact on the application's performance.
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Adhinarayanan, Vignesh. "Models and Techniques for Green High-Performance Computing." Diss., Virginia Tech, 2020. http://hdl.handle.net/10919/98660.
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High-performance computing (HPC) systems have become power limited. For instance, the U.S. Department of Energy set a power envelope of 20MW in 2008 for the first exascale supercomputer now expected to arrive in 2021--22. Toward this end, we seek to improve the greenness of HPC systems by improving their performance per watt at the allocated power budget.
In this dissertation, we develop a series of models and techniques to manage power at micro-, meso-, and macro-levels of the system hierarchy, specifically addressing data movement and heterogeneity. We target the chip interconnect at the micro-level, heterogeneous nodes at the meso-level, and a supercomputing cluster at the macro-level. Overall, our goal is to improve the greenness of HPC systems by intelligently managing power.
The first part of this dissertation focuses on measurement and modeling problems for power. First, we study how to infer chip-interconnect power by observing the system-wide power consumption. Our proposal is to design a novel micro-benchmarking methodology based on data-movement distance by which we can properly isolate the chip interconnect and measure its power. Next, we study how to develop software power meters to monitor a GPU's power consumption at runtime. Our proposal is to adapt performance counter-based models for their use at runtime via a combination of heuristics, statistical techniques, and application-specific knowledge.
In the second part of this dissertation, we focus on managing power. First, we propose to reduce the chip-interconnect power by proactively managing its dynamic voltage and frequency (DVFS) state. Toward this end, we develop a novel phase predictor that uses approximate pattern matching to forecast future requirements and in turn, proactively manage power. Second, we study the problem of applying a power cap to a heterogeneous node. Our proposal proactively manages the GPU power using phase prediction and a DVFS power model but reactively manages the CPU. The resulting hybrid approach can take advantage of the differences in the capabilities of the two devices. Third, we study how in-situ techniques can be applied to improve the greenness of HPC clusters.
Overall, in our dissertation, we demonstrate that it is possible to infer power consumption of real hardware components without directly measuring them, using the chip interconnect and GPU as examples. We also demonstrate that it is possible to build models of sufficient accuracy and apply them for intelligently managing power at many levels of the system hierarchy.Doctor of Philosophy
Past research in green high-performance computing (HPC) mostly focused on managing the power consumed by general-purpose processors, known as central processing units (CPUs) and to a lesser extent, memory. In this dissertation, we study two increasingly important components: interconnects (predominantly focused on those inside a chip, but not limited to them) and graphics processing units (GPUs). Our contributions in this dissertation include a set of innovative measurement techniques to estimate the power consumed by the target components, statistical and analytical approaches to develop power models and their optimizations, and algorithms to manage power statically and at runtime. Experimental results show that it is possible to build models of sufficient accuracy and apply them for intelligently managing power on multiple levels of the system hierarchy: chip interconnect at the micro-level, heterogeneous nodes at the meso-level, and a supercomputing cluster at the macro-level.
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Safieddine, Ibrahim. "Optimisation d'infrastructures de cloud computing sur des green datacenters." Thesis, Université Grenoble Alpes (ComUE), 2015. http://www.theses.fr/2015GREAM083/document.
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Les centres de données verts de dernière génération ont été conçus pour une consommation optimisée et une meilleure qualité du niveau de service SLA. Cependant,ces dernières années, le marché des centres de données augmente rapidement,et la concentration de la puissance de calcul est de plus en plus importante, ce qui fait augmenter les besoins en puissance électrique et refroidissement. Un centre de données est constitué de ressources informatiques, de systèmes de refroidissement et de distribution électrique. De nombreux travaux de recherche se sont intéressés à la réduction de la consommation des centres de données afin d'améliorer le PUE, tout en garantissant le même niveau de service. Certains travaux visent le dimensionnement dynamique des ressources en fonction de la charge afin de réduire le nombre de serveurs démarrés, d'autres cherchent à optimiser le système de refroidissement qui représente un part important de la consommation globale.Dans cette thèse, afin de réduire le PUE, nous étudions la mise en place d'un système autonome d'optimisation globale du refroidissement, qui se base sur des sources de données externes tel que la température extérieure et les prévisions météorologiques, couplé à un module de prédiction de charge informatique globale pour absorber les pics d'activité, pour optimiser les ressources utilisés à un moindre coût, tout en préservant la qualité de service. Afin de garantir un meilleur SLA, nous proposons une architecture distribuée pour déceler les anomalies de fonctionnements complexes en temps réel, en analysant de gros volumes de données provenant des milliers de capteurs du centre de données. Détecter les comportements anormaux au plus tôt, permet de réagir plus vite face aux menaces qui peuvent impacter la qualité de service, avec des boucles de contrôle autonomes qui automatisent l'administration. Nous évaluons les performances de nos contributions sur des données provenant d'un centre de donnée en exploitation hébergeant des applications réellesNext-generation green datacenters were designed for optimized consumption and improved quality of service level Service Level Agreement (SLA). However, in recent years, the datacenter market is growing rapidly, and the concentration of the computing power is increasingly important, thereby increasing the electrical power and cooling consumptions. A datacenter consists of computing resources, cooling systems, and power distribution. Many research studies have focused on reducing the consumption of datacenters to improve the PUE, while guaranteeing the same level of service. Some works aims the dynamic sizing of resources according to the load, to reduce the number of started servers, others seek to optimize the cooling system which represents an important part of total consumption. In this thesis, in order to reduce the PUE, we study the design of an autonomous system for global cooling optimization, which is based on external data sources such as the outside temperature and weather forecasting, coupled with an overall IT load prediction module to absorb the peaks of activity, to optimize activere sources at a lower cost while preserving service level quality. To ensure a better SLA, we propose a distributed architecture to detect the complex operation anomalies in real time, by analyzing large data volumes from thousands of sensors deployed in the datacenter. Early identification of abnormal behaviors, allows a better reactivity to deal with threats that may impact the quality of service, with autonomous control loops that automate the administration. We evaluate the performance of our contributions on data collected from an operating datacenter hosting real applications
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Tapou, Monaf Sabri. "High efficiency smart voltage regulating module for green mobile computing." Thesis, Brunel University, 2014. http://bura.brunel.ac.uk/handle/2438/8285.
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In this thesis a design for a smart high efficiency voltage regulating module capable of supplying the core of modern microprocessors incorporating dynamic voltage and frequency scaling (DVS) capability is accomplished using a RISC based microcontroller to facilitate all the functions required to control, protect, and supply the core with the required variable operating voltage as set by the DVS management system. Normally voltage regulating modules provide maximum power efficiency at designed peak load, and the efficiency falls off as the load moves towards lesser values. A mathematical model has been derived for the main converter and small signal analysis has been performed in order to determine system operation stability and select a control scheme that would improve converter operation response to transients and not requiring intense computational power to realize. A Simulation model was built using Matlab/Simulink and after experimenting with tuned PID controller and fuzzy logic controllers, a simple fuzzy logic control scheme was selected to control the pulse width modulated converter and several methods were devised to reduce the requirements for computational power making the whole system operation realizable using a low power RISC based microcontroller. The same microcontroller provides circuit adaptations operation in addition to providing protection to load in terms of over voltage and over current protection. A novel circuit technique and operation control scheme enables the designed module to selectively change some of the circuit elements in the main pulse width modulated buck converter so as to improve efficiency over a wider range of loads. In case of very light loads as the case when the device goes into standby, sleep or hibernation mode, a secondary converter starts operating and the main converter stops. The secondary converter adapts a different operation scheme using switched capacitor technique which provides high efficiency at low load currents. A fuzzy logic control scheme was chosen for the main converter for its lighter computational power requirement promoting implementation using ultra low power embedded controllers. Passive and active components were carefully selected to augment operational efficiency. These aspects enabled the designed voltage regulating module to operate with efficiency improvement in off peak load region in the range of 3% to 5%. At low loads as the case when the computer system goes to standby or sleep mode, the efficiency improvent is better than 13% which will have noticeable contribution in extending battery run time thus contributing to lowering the carbon footprint of human consumption.
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Sacchetti, Nicola. "Green information technology." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2011. http://amslaurea.unibo.it/1861/.
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Quando si parla di green information technology si fa riferimento a un nuovo filone di ricerche focalizzate sulle tecnologie ecologiche o verdi rivolte al rispetto ambientale.
In prima battuta ci si potrebbe chiedere quali siano le reali motivazioni che possono portare allo studio di tecnologie green nel settore dell’information technology: sono così inquinanti i computer? Non sono le automobili, le industrie, gli aerei, le discariche ad avere un impatto inquinante maggiore sull’ambiente?
Certamente sì, ma non bisogna sottovalutare l’impronta inquinante settore IT; secondo una recente indagine condotta dal centro di ricerche statunitense Gartner nel 2007, i sistemi IT sono tra le maggiori fonti di emissione di CO2 e di altri gas a effetto serra , con una percentuale del 2% sulle emissioni totali del pianeta, eguagliando il tasso di inquinamento del settore aeromobile. Il numero enorme di computer disseminato in tutto il mondo assorbe ingenti quantità di energia elettrica e le centrali che li alimentano emettono tonnellate di anidride carbonica inquinando l’atmosfera.
Con questa tesi si vuole sottolineare l’impatto ambientale del settore verificando, attraverso l’analisi del bilancio sociale ed ambientale, quali misure siano state adottate dai leader del settore informatico.
La ricerca è volta a dimostrare che le più grandi multinazionali informatiche siano consapevoli dell’inquinamento prodotto, tuttavia non adottano abbastanza soluzioni per limitare le emissioni, fissando futili obiettivi futuri.
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Letcher, Charles. "Green computing - Desktop computer power management at the city of Tulsa." Thesis, Oklahoma State University, 2013. http://pqdtopen.proquest.com/#viewpdf?dispub=1542205.
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One type of Green Computing focuses on reducing power consumption of computers. Specialized software like 1E/Nightwatchman aids in reducing the power consumption of desktop computers by placing them in a low power state when not in use. This thesis describes the implementation of 1E/Nightwatchman power management software on two thousand desktop computers at the City of Tulsa. It shows the method used to predict power savings of $100,000.00 per year and compares the prediction to the actual savings after one year of operation.
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Aldawsari, B. M. A. "An energy-efficient multi-cloud service broker for green cloud computing environment." Thesis, Liverpool John Moores University, 2018. http://researchonline.ljmu.ac.uk/7954/.
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The heavy demands on cloud computing resources have led to a substantial growth in energy consumption of the data transferred between cloud computing parties (i.e., providers, datacentres, users, and services) and in datacentre’s services due to the increasing loads on these services. From one hand, routing and transferring large amounts of data into a datacentre located far from the user’s geographical location consume more energy than just processing and storing the same data on the cloud datacentre. On the other hand, when a cloud user submits a job (in the form of a set of functional and non-functional requirements) to a cloud service provider (aka, datacentre) via a cloud services broker; the broker becomes responsible to find the best-fit service to the user request based mainly on the user’s requirements and Quality of Service (QoS) (i.e., response time, latency). Hence, it becomes a high necessity to locate the lowest energy consumption route between the user and the designated datacentre; and the minimum possible number of most energy efficient services that satisfy the user request. In fact, finding the most energy-efficient route to the datacentre, and most energy efficient service(s) to the user are the biggest challenges of multi-cloud broker’s environment. This thesis presents and evaluates a novel multi-cloud broker solution that contains three innovative models and their associated algorithms. The first one is aimed at finding the most energy efficient route, among multiple possible routes, between the user and cloud datacentre. The second model is to find and provide the lowest possible number of most energy efficient services in order to minimise data exchange based on a bin-packing approach. The third model creates an energy-aware composition plan by integrating the most energy efficient services, in order to fulfil user requirements. The results demonstrated a favourable performance of these models in terms of selecting the most energy efficient route and reaching the least possible number of services for an optimum and energy efficient composition.
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McClurg, Josiah. "Fast demand response with datacenter loads: a green dimension of big data." Diss., University of Iowa, 2017. https://ir.uiowa.edu/etd/5811.
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Demand response is one of the critical technologies necessary for allowing large-scale penetration of intermittent renewable energy sources in the electric grid. Data centers are especially attractive candidates for providing flexible, real-time demand response services to the grid because they are capable of fast power ramp-rates, large dynamic range, and finely-controllable power consumption. This thesis makes a contribution toward implementing load shaping with server clusters through a detailed experimental investigation of three broadly-applicable datacenter workload scenarios. We experimentally demonstrate the eminent feasibility of datacenter demand response with a distributed video transcoding application and a simple distributed power controller. We also show that while some software power capping interfaces performed better than others, all the interfaces we investigated had the high dynamic range and low power variance required to achieve high quality power tracking. Our next investigation presents an empirical performance evaluation of algorithms that replace arithmetic operations with low-level bit operations for power-aware Big Data processing. Specifically, we compare two different data structures in terms of execution time and power efficiency: (a) a baseline design using arrays, and (b) a design using bit-slice indexing (BSI) and distributed BSI arithmetic. Across three different datasets and three popular queries, we show that the bit-slicing queries consistently outperform the array algorithm in both power efficiency and execution time. In the context of datacenter power shaping, this performance optimization enables additional power flexibility -- achieving the same or greater performance than the baseline approach, even under power constraints. The investigation of read-optimized index queries leads up to an experimental investigation of the tradeoffs among power constraint, query freshness, and update aggregation size in a dynamic big data environment. We compare several update strategies, presenting a bitmap update optimization that allows improved performance over both a baseline approach and an existing state-of-the-art update strategy. Performing this investigation in the context of load shaping, we show that read-only range queries can be served without performance impact under power cap, and index updates can be tuned to provide a flexible base load. This thesis concludes with a brief discussion of control implementation and summary of our findings.
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Mei, Xinxin. "Energy conservation techniques for GPU computing." HKBU Institutional Repository, 2016. https://repository.hkbu.edu.hk/etd_oa/298.
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The emerging general purpose graphics processing units (GPGPU) computing has tremendously speeded up a great variety of commercial and scientific applications. The GPUs have become prevalent accelerators in current high performance clusters. Though the computational capacity per Watt of the GPUs is much higher than that of the CPUs, the hybrid GPU clusters still consume enormous power. To conserve energy on this kind of clusters is of critical significance. In this thesis, we seek energy conservative computing on the GPU accelerated servers. We introduce our studies as follows. First, we dissect the GPU memory hierarchy due to the fact that most of the GPU applications are suffering from the GPU memory bottleneck. We find that the conventional CPU cache models cannot be applied on the modern GPU caches, and the microbenchmarks to study the conventional CPU cache become invalid for the GPU. We propose the GPU-specified microbenchmarks to examine the GPU memory structures and properties. Our benchmark results verify that the design goal of the GPU has transformed from pure computation performance to better energy efficiency. Second, we investigate the impact of dynamic voltage and frequency scaling (DVFS), a successful energy management technique for CPUs, on the GPU platforms. Our experimental results suggest that GPU DVFS is still promising in conserving energy, but the patterns to save energy strongly differ from those of the CPU. Besides, the effect of GPU DVFS depends on the individual application characteristics. Third, we derive the GPU DVFS power and performance models from our experimental results, based on which we find the optimal GPU voltage and frequency setting to minimize the energy consumption of a single GPU task. We then study the problem of scheduling multiple tasks on a hybrid CPU-GPU cluster to minimize the total energy consumption by GPU DVFS. We design an effective offline scheduling algorithm which can reduce the energy consumption significantly. At last, we combine the GPU DVFS and dynamic resource sleep (DRS), another energy management technique, to further conserve the energy, for the online task scheduling on hybrid clusters. Though the idle energy consumption increases significantly compared to the offline problem, our online scheduling algorithm still achieves more than 30% of energy conservation with appropriate runtime GPU DVFS readjustments.
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Strachota, Marek. "Technologické a funkční inovativní trendy ERP." Master's thesis, Vysoká škola ekonomická v Praze, 2015. http://www.nusl.cz/ntk/nusl-193056.
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Current trends in ERP system were studied by conducting research and analyzes to see to what degree are current ERP trends reflected in existing ERP solutions that are being developed by both Czech and multinational vendors. For the purposes of the research a set of hypotheses was formulated and used to analyze the selected solutions. The research found two trends that are represented in the majority of selected ERP solutions. The application of cloud computing technology and the suitability to use particular solutions as two-tiered ERP. It was also found that all researched vendors to a certain degree implement the principles of Green ICT, although no vendor specifically labeled their software as Green ERP. It was also found that the term Social ERP doesn't appear to be an acceptable term for ERP vendors, although Social ERP functionality of some degree was found to be present in ERP solutions from multinational vendors.
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Nazari, Gholamreza, and Hooman Karim. "Mission Possible: Becoming Green and Sustainable : An empirical study on Green IT Adoption and underlying factors influencing it." Thesis, Mälardalens högskola, Akademin för hållbar samhälls- och teknikutveckling, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-14036.
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This study aims to investigate the main areas of Green IT and to determine which areas of Green IT have been widely adopted and implemented in our case studies. The purpose of the proposed study is also to identify, describe and analyze underlying factors that are perceived to be important to the adoption and implementation of Green IT. Finally, this research attempts to examine which factors are more important in our two case studies, Västerås City Stad and Mälardalen University.
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Do, Manh Duc. "Green Cloud - Load Balancing, Load Consolidation using VM Migration." TopSCHOLAR®, 2017. https://digitalcommons.wku.edu/theses/2059.
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Recently, cloud computing is a new trend emerging in computer technology with a massive demand from the clients. To meet all requirements, a lot of cloud data centers have been constructed since 2008 when Amazon published their cloud service. The rapidly growing data center leads to the consumption of a tremendous amount of energy even cloud computing has better improved in the performance and energy consumption, but cloud data centers still absorb an immense amount of energy. To raise company’s income annually, the cloud providers start considering green cloud concepts which gives an idea about how to optimize CPU’s usage while guaranteeing the quality of service. Many cloud providers are paying more attention to both load balancing and load consolidation which are two significant components of a cloud data center.
Load balancing is taken into account as a vital part of managing income demand, improving the cloud system’s performance. Live virtual machine migration is a technique to perform the dynamic load balancing algorithm. To optimize the cloud data center, three issues are considered: First, how does the cloud cluster distribute the virtual machine (VM) requests from clients to all physical machine (PM) when each computer has a different capacity. Second, what is the solution to make CPU’s usage of all PMs to be nearly equal? Third, how to handle two extreme scenarios: rapidly rising CPU’s usage of a PM due to sudden massive workload requiring VM migration immediately and resources expansion to respond to substantial cloud cluster through VM requests. In this chapter, we provide an approach to work with those issues in the implementation and results. The results indicated that the performance of the cloud cluster was improved significantly.
Load consolidation is the reverse process of load balancing which aims to provide sufficient cloud servers to handle the client requests. Based on the advance of live VM migration, cloud data center can consolidate itself without interrupting the cloud service, and superfluous PMs are turned to save mode to reduce the energy consumption. This chapter provides a solution to approach load consolidation including implementation and simulation of cloud servers.
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Yaw, Yi Xin. "Murdoch University science and computing building energy simulation & mechanical engineering green building design." Thesis, Yaw, Yi Xin (2015) Murdoch University science and computing building energy simulation & mechanical engineering green building design. Honours thesis, Murdoch University, 2015. https://researchrepository.murdoch.edu.au/id/eprint/29904/.
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Anchored in teaching, research and community engagement approaches, Murdoch University is setting up the development of a symbolic new mixed use campus precinct expansion which is listed as one of Murdoch University’s strategic plan. As stated above, a part of the strategic plan includes the development of a new Mechanical Engineering Building (MEB) in order to engage future Mechanical Engineering students. This newly proposed MEB would be designed and constructed as an extension building from the existing Science and Computing Building that is located at the Murdoch South Street campus. Hence, the major focus of this research study investigate the new Murdoch University Mechanical Engineering green building structure and design by analysing the energy consumption of the existing Science and Computing building.
The annual energy consumption of the existing building is obtained through the identification of construction materials, building design and building operational activities. All this information is then simulated using Virtual Environment by Integrated Environmental Solutions (IES-VE). The outline of this IES-VE modelling tool and implementation procedures is illustrated in Chapter 3 (Methodology) and the simulation results used to identify the major sources of the energy use are included in Chapter 4 (Results). The results showed the massive energy consumption that being used in the current Science and Computing building and the annual energy consumption is broken down into different components that makes up the total energy use.Moreover, the possibilities for building energy consumption reduction are discussed and this is based on the low embodied energy building materials and low existing building operational energy reduction strategies.
For the sake of achieving green star building standard, NABERS self rating tools are introduced by determining the building operational routines and its design structure. The existing building’s NABERS score will be recognised as a useful measure for the new MEB design ideas and the selection of appliances used in order to achieve the low energy building objectives.
Furthermore, the structure and design of the new MEB are drafted based on the essential requirements using SketchUp drawing tool. The dimensions and working purpose of each individual floor are illustrated and reviewed. On the other hand, basic specifications of the MEB such as experimentation and research laboratory requirements, computer appliances and HVAC demands are determined in order to diagnose the NABERS rating and thus establish a new target for green building achievement. The estimated new building energy consumption is generated and possible strategies which include energy efficiency design, energy efficient technologies and renewable technologies are discussed in Chapter 5.
Generally, a green building is achieved through an integration of energy efficient programs and environmentally friendly construction projects. Thus, an introduction of potential sustainable strategies is illustrated in Chapter 6 in order to develop Murdoch University into a carbon-neutral community. The potential sustainable strategies that are discussed in this thesis project included rainwater harvesting technology, wastewater treatment plants, timber prefabricated construction and green roof garden implementation. Lastly, project summary is included in Chapter 6 (Conclusion) and several recommendations are discussed that would be important to be evaluated and discussed for further improvement.
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Khargharia, Bithika. "Adaptive Power and Performance Management of Computing Systems." Diss., The University of Arizona, 2008. http://hdl.handle.net/10150/193653.
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With the rapid growth of servers and applications spurred by the Internet economy, power consumption in today's data centers is reaching unsustainable limits. This has led to an imminent financial, technical and environmental crisis that is impacting the society at large. Hence, it has become critically important that power consumption be efficiently managed in these computing power-houses of today. In this work, we revisit the issue of adaptive power and performance management of data center server platforms. Traditional data center servers are statically configured and always over-provisioned to be able to handle peak load. We transform these statically configured data center servers to clairvoyant entities that can sense changes in the workload and dynamically scale in capacity to adapt to the requirements of the workload. The over-provisioned server capacity is transitioned to low-power states and they remain in those states for as long as the performance remains within given acceptable thresholds. The platform power expenditure is minimized subject to performance constraints. This is formulated as a performance-per-watt optimization problem and solved using analytical power and performance models. Coarse-grained optimizations at the platform-level are refined by local optimizations at the devices-level namely - the processor & memory subsystems. Our adaptive interleaving technique for memory power management yielded about 48.8% (26.7 kJ) energy savings compared to traditional techniques measured at 4.5%. Our adaptive platform power and performance management technique demonstrated 56.25% energy savings for memory-intensive workload, 63.75% savings for processor-intensive workload and 47.5% savings for a mixed workload while maintaining platform performance within given acceptable thresholds.
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Subramaniam, Balaji. "Metrics, Models and Methodologies for Energy-Proportional Computing." Diss., Virginia Tech, 2015. http://hdl.handle.net/10919/56492.
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Massive data centers housing thousands of computing nodes have become commonplace in enterprise computing, and the power consumption of such data centers is growing at an unprecedented rate. Exacerbating such costs, data centers are often over-provisioned to avoid costly outages associated with the potential overloading of electrical circuitry. However, such over provisioning is often unnecessary since a data center rarely operates at its maximum capacity. It is imperative that we realize effective strategies to control the power consumption of the server and improve the energy efficiency of data centers. Adding to the problem is the inability of the servers to exhibit energy proportionality which diminishes the overall energy efficiency of the data center. Therefore in this dissertation, we investigate whether it is possible to achieve energy proportionality at the server- and cluster-level by efficient power and resource provisioning. Towards this end, we provide a thorough analysis of energy proportionality at the server and cluster-level and provide insight into the power saving opportunity and mechanisms to improve energy proportionality.
Specifically, we make the following contribution at the server-level using enterprise-class workloads. We analyze the average power consumption of the full system as well as the subsystems and describe the energy proportionality of these components, characterize the instantaneous power profile of enterprise-class workloads using the on-chip energy meters, design a runtime system based on a load prediction model and an optimization framework to set the appropriate power constraints to meet specific performance targets and then present the effects of our runtime system on energy proportionality, average power, performance and instantaneous power consumption of enterprise applications. We then make the following contributions at the cluster-level. Using data serving, web searching and data caching as our representative workloads, we first analyze the component-level power distribution on a cluster. Second, we characterize how these workloads utilize the cluster. Third, we analyze the potential of power provisioning techniques (i.e., active low-power, turbo and idle low-power modes) to improve the energy proportionality. We then describe the ability of active low-power modes to provide trade-offs in power and latency. Finally, we compare and contrast power provisioning and resource provisioning techniques.
This thesis sheds light on mechanisms to tune the power provisioned for a system under strict performance targets and opportunities to improve energy proportionality and instantaneous power consumption via efficient power and resource provisioning at the server- and cluster-level.Ph. D.
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Junior, Osvaldo Adilson de Carvalho. "GreenMACC - Uma arquitetura para metaescalonamento verde com provisão de QoS em uma nuvem privada." Universidade de São Paulo, 2014. http://www.teses.usp.br/teses/disponiveis/55/55134/tde-08042015-161656/.
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Esta tese de Doutorado tem como objetivo apresentar uma arquitetura para metaescalonamento verde com provisão de qualidade de serviço em uma nuvem privada denominada GreenMACC. Essa nova arquitetura oferece a automatização na escolha de políticas em quatro estágios de escalonamento de uma nuvem privada, permitindo cumprir a negociação que foi estabelecida com o usuário. Devido a essa função, é possível garantir que o GreenMACC se comporte seguindo os princípios da computação verde sem deixar de se preocupar com a qualidade do serviço. Nesta tese o GreenMACC é apresentado, detalhado, discutido, validado e avaliado. Com os resultados apresentados pode-se concluir que a arquitetura proposta mostrou-se consistente, permitindo a execução dos serviços requisitados com diversas políticas de escalonamento em todos os seus estágios. Além disso, demonstrou flexibilidade em receber novas políticas, com focos verde e de qualidade de serviço, e eficiência na escolha das políticas de escalonamento de acordo com a negociação feita com o usuário.This PhD thesis aims to present an architecture for green metascheduling with provision of quality of service in a private cloud called GreenMACC. This new architecture offers the possibility of choosing automatically the four stage scheduling policies of a private cloud, allowing to reach the users negotiation. As a result of this function, it is possible to ensure that GreenMACCs behavior follows the green computing principles and also is worried about the quality of the service. In this thesis Green- MACC is presented, particularized, discussed, validated and evaluated. The results show that the proposed architecture is consistent, allowing the execution of the requested services considering various scheduling policies in the stages. Moreover, GreenMACC proves to be flexible as allows new policies, focusing on green and quality of service, and to be efficient as chooses the scheduling policies following the users negotiation.
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Da, Silva Ralston A. "Green Computing – Power Efficient Management in Data Centers Using Resource Utilization as a Proxy for Power." The Ohio State University, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=osu1259760420.
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Vojtková, Erika. "Trendy v oblasti podnikových IS - Green IT." Master's thesis, Vysoká škola ekonomická v Praze, 2011. http://www.nusl.cz/ntk/nusl-82021.
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The theme of this thesis is one of the latest trends in IT -- Green IT. For companies implementation of green IT means not only acknowledging its responsibility towards society and environment, but also substantial financial benefits and improved public perception of their business. There are several motivations for companies to go green. Green IT initiatives are increasingly supported by the legislation and various standards. Different procedures and approaches to help companies in their transformation are developing as well. The objectives of this thesis include the identification of key players, the benefits and barriers to green IT, and new opportunities. The aim of this thesis is to bring a comprehensive view of the green IT trend and provide enough quality information to obtain an overall view of the green IT trend and a possible basis for deeper interest in the subject. Another objective is to analyze the frameworks used for the implementation of green IT initiatives in organizations. The achievement is approached through research and analysis, and information available in the literature, published reports and websites dealing with green IT were used. Thesis contribution lies particularly in analysis of green IT frameworks, within which there was evaluated their interests in terms of green IT waves, green IT objectives, their use in the process of implementation green IT solutions, their locus and other attributes.
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Chinenyeze, Samuel Jaachimma. "Mango : a model-driven approach to engineering green Mobile Cloud Applications." Thesis, Edinburgh Napier University, 2017. http://researchrepository.napier.ac.uk/Output/976572.
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With the resource constrained nature of mobile devices and the resource abundant offerings of the cloud, several promising optimisation techniques have been proposed by the green computing research community. Prominent techniques and unique methods have been developed to offload resource/computation intensive tasks from mobile devices to the cloud. Most of the existing offloading techniques can only be applied to legacy mobile applications as they are motivated by existing systems. Consequently, they are realised with custom runtimes which incur overhead on the application. Moreover, existing approaches which can be applied to the software development phase, are difficult to implement (based on manual process) and also fall short of overall (mobile to cloud) efficiency in software qualityattributes or awareness of full-tier (mobile to cloud) implications. To address the above issues, the thesis proposes a model-driven architecturefor integration of software quality with green optimisation in Mobile Cloud Applications (MCAs), abbreviated as Mango architecture. The core aim of the architecture is to present an approach which easily integrates software quality attributes (SQAs) with the green optimisation objective of Mobile Cloud Computing (MCC). Also, as MCA is an application domain which spans through the mobile and cloud tiers; the Mango architecture, therefore, takesinto account the specification of SQAs across the mobile and cloud tiers, for overall efficiency. Furthermore, as a model-driven architecture, models can be built for computation intensive tasks and their SQAs, which in turn drives the development – for development efficiency. Thus, a modelling framework (called Mosaic) and a full-tier test framework (called Beftigre) were proposed to automate the architecture derivation and demonstrate the efficiency of Mango approach. By use of real world scenarios/applications, Mango has been demonstrated to enhance the MCA development process while achieving overall efficiency in terms of SQAs (including mobile performance and energy usage compared to existing counterparts).
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Townsend, Jack H. "Digital systems for sustainability : a classification of ICT4S and smart green startups distinguishing automation, social computing and cleantech push." Thesis, University of Southampton, 2017. https://eprints.soton.ac.uk/424894/.
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Amongst the many innovations of the digital industry have been systems termed “smart green”, “cleanweb” or “Sustainability by ICT” that enable more sustainable patterns of production and consumption. The field of ICT for Sustainability (ICT4S) has developed conceptualisations of these systems such as the LES Model that describes their “enabling impacts” upon production and consumption. However, initial action research amongst cleanweb startups suggested that important groups of smart green system are not distinguished by existing conceptualisations, notably the highly social systems with many interacting users, and the systems that support the adoption of more sustainable products. To address these limitations with existing conceptualisations of ICT4S, a qualitative analysis was undertaken of cleanweb companies, mapping out the range of possibilities being explored by the industry. 500 company descriptions were analysed, primarily from the CrunchBase online database. A list of search terms was developed to identify the most relevant companies. Significant characteristics of the companies were coded, and the codes were then sorted and resorted to identify higher-level concepts and categories, refined by classifying new samples, and modelled by diagramming. The result, and main contribution, is a typology of the enabling impacts of smart green systems termed the “Smart Green Map” (SGM) that organises them along five dimensions. Digital systems were found to decouple resource use either by “saving” resources directly through efficiency, or otherwise indirectly by “pushing cleantech” i.e. enhancing the adoption, construction and operation of more sustainable products. This dichotomy forms a dimension of the SGM called “Decoupling Directness”. The contrasting mechanisms of “saving” and “pushing” were modelled with the LES Model’s resource-use hierarchy theory. The new “push” category of enabling impacts of DDS was not clearly distinguished by established conceptualisations of ICT4S. These push impacts work by actually increasing consumption of certain products such as solar panels, bicycles, or home insulation. A fresh sample of cleanweb companies and ICT4S research papers was then classified with the SGM, to assess its utility for research. Classification by Decoupling Directness found that, as hypothesised, whilst “push systems” comprised half of the startups, they made up only 18% of research papers. Digital systems were found to combine people and digital technology in four contrasting ways, termed the “Enablers”: “Automation” is purely technological with little human involvement; “Augmentation” supports and shapes the actions of one main user; “Coordination” supports the communication, interaction and collective action of many users; whilst “Autination” – a term proposed here for “automated coordination” – automates interactions between human actors. These four Enablers are the cells of a 2x2 matrix whose axes are “level of automation” and “level of social interaction”, two further dimensions of the SGM. A venture capital firm has used the Enablers as the basis for their investment framework, informing decisions and communicating policies to investors and the wider market, as described in a case study. The processes of production and consumption by which resource use is decoupled were best described as part of the Circular Economy. These processes form a further dimension of the SGM that situates recycling, reuse and maintenance within ICT4S, and Sharing Economy systems such as tool-sharing and ride-sharing platforms. The remaining dimension of the SGM is the type of resource, such as heat energy, water or materials.
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Orgerie, Anne-Cécile. "An Energy-Efficient Reservation Framework for Large-Scale Distributed Systems." Phd thesis, Ecole normale supérieure de lyon - ENS LYON, 2011. http://tel.archives-ouvertes.fr/tel-00672130.
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Over the past few years, the energy consumption of Information and Communication Technologies (ICT) has become a major issue. Nowadays, ICT accounts for 2% of the global CO2 emissions, an amount similar to that produced by the aviation industry. Large-scale distributed systems (e.g. Grids, Clouds and high-performance networks) are often heavy electricity consumers because -- for high-availability requirements -- their resources are always powered on even when they are not in use. Reservation-based systems guarantee quality of service, allow for respect of user constraints and enable fine-grained resource management. For these reasons, we propose an energy-efficient reservation framework to reduce the electric consumption of distributed systems and dedicated networks. The framework, called ERIDIS, is adapted to three different systems: data centers and grids, cloud environments and dedicated wired networks. By validating each derived infrastructure, we show that significant amounts of energy can be saved using ERIDIS in current and future large-scale distributed systems.
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Targa, Jan. "Analýza přístupů k tématice Green ICT v IT společnostech operujících na českém trhu." Master's thesis, Vysoká škola ekonomická v Praze, 2011. http://www.nusl.cz/ntk/nusl-81992.
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Recent economical crises, constant development of new technologies and faster globalisation cause different changes in all organisations all over the world. One of these changes are also different considerations about suistainable development and the impact different companies have. Those organisations are getting more and more involved into this topic and become more competitive within quickly developing global economics. They look for the ways how to contribute to suistainable development. One of the ways is also suistainable IT in a company focused on Green ICT. The aim of this thesis is to describe Green ICT, how it matches with suistainable development and what are the areas it covers. Firstly, the thesis contains an explanation of what Green ICT is. Secondly it focuses on the approach to this issue in different companies of different sizes in different industries. To achieve this aim, there are used different surveys from worldwide known companies. In the next part this thesis deals with two most important global IT companies, that significantly influence supply of ERP systems to the Czech market. This part specifies the areas covered by above mentioned companies and their main achievements. The main goal of this thesis is to analyze current state of Green ICT within local market. To achieve this goal, there was taken a survey focusing on Green ICT perception at ERP suppliers on the Czech market. Data from this survey were then analysed and evaluated. This thesis also provides a measuring scale for evaluation of Green ICT level. To demonstrate this, there were two global companies evaluated compared to three local companies evaluation.
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García-Martín, Eva. "Extraction and Energy Efficient Processing of Streaming Data." Licentiate thesis, Blekinge Tekniska Högskola, Institutionen för datalogi och datorsystemteknik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-15532.
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The interest in machine learning algorithms is increasing, in parallel with the advancements in hardware and software required to mine large-scale datasets. Machine learning algorithms account for a significant amount of energy consumed in data centers, which impacts the global energy consumption. However, machine learning algorithms are optimized towards predictive performance and scalability. Algorithms with low energy consumption are necessary for embedded systems and other resource constrained devices; and desirable for platforms that require many computations, such as data centers. Data stream mining investigates how to process potentially infinite streams of data without the need to store all the data. This ability is particularly useful for companies that are generating data at a high rate, such as social networks. This thesis investigates algorithms in the data stream mining domain from an energy efficiency perspective. The thesis comprises of two parts. The first part explores how to extract and analyze data from Twitter, with a pilot study that investigates a correlation between hashtags and followers. The second and main part investigates how energy is consumed and optimized in an online learning algorithm, suitable for data stream mining tasks. The second part of the thesis focuses on analyzing, understanding, and reformulating the Very Fast Decision Tree (VFDT) algorithm, the original Hoeffding tree algorithm, into an energy efficient version. It presents three key contributions. First, it shows how energy varies in the VFDT from a high-level view by tuning different parameters. Second, it presents a methodology to identify energy bottlenecks in machine learning algorithms, by portraying the functions of the VFDT that consume the largest amount of energy. Third, it introduces dynamic parameter adaptation for Hoeffding trees, a method to dynamically adapt the parameters of Hoeffding trees to reduce their energy consumption. The results show an average energy reduction of 23% on the VFDT algorithm.Scalable resource-efficient systems for big data analytics
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Ahvar, Ehsan. "Cost-efficient resource allocation for green distributed clouds." Thesis, Evry, Institut national des télécommunications, 2017. http://www.theses.fr/2017TELE0001.
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L'objectif de cette thèse est de présenter de nouveaux algorithmes de placement de machines virtuelles (VMs) à fin d’optimiser le coût et les émissions de carbone dans les Clouds distribués. La thèse se concentre d’abord sur la rentabilité des Clouds distribués, et développe ensuite les raisons d’optimiser les coûts ainsi que les émissions de carbone. La thèse comprend deux principales parties: la première propose, développe et évalue les algorithmes de placement statiques de VMs (où un premier placement d'une VM détient pendant toute la durée de vie de la VM). La deuxième partie propose des algorithmes de placement dynamiques de VMs où le placement initial de VM peut changer dynamiquement (par exemple, grâce à la migration de VMs et à leur consolidation). Cette thèse comprend cinq contributions. La première contribution est une étude de l'état de l'art sur la répartition des coûts et des émissions de carbone dans les environnements de clouds distribués. La deuxième contribution propose une méthode d'allocation des ressources, appelée NACER, pour les clouds distribués. L'objectif est de minimiser le coût de communication du réseau pour exécuter une tâche dans un cloud distribué. La troisième contribution propose une méthode de placement VM (appelée NACEV) pour les clouds distribués. NACEV est une version étendue de NACER. Tandis que NACER considère seulement le coût de communication parmi les DCs, NACEV optimise en même temps les coûts de communication et de calcul. Il propose également un algorithme de cartographie pour placer des machines virtuelles sur des machines physiques (PM). La quatrième contribution présente une méthode de placement VM efficace en termes de coûts et de carbone (appelée CACEV) pour les clouds distribués verts. CACEV est une version étendue de NACEV. En plus de la rentabilité, CACEV considère l'efficacité des émissions de carbone pour les clouds distribués. Pour obtenir une meilleure performance, la cinquième contribution propose une méthode dynamique de placement VM (D-CACEV) pour les clouds distribués. D-CACEV est une version étendue de notre travail précédent, CACEV, avec des chiffres supplémentaires, une description et également des mécanismes de migration de VM en direct. Nous montrons que notre mécanisme conjoint de réallocation-placement de VM peut constamment optimiser à la fois le coût et l'émission de carbone dans un cloud distribuéVirtual machine (VM) placement (i.e., resource allocation) method has a direct effect on both cost and carbon emission. Considering the geographic distribution of data centers (DCs), there are a variety of resources, energy prices and carbon emission rates to consider in a distributed cloud, which makes the placement of VMs for cost and carbon efficiency even more critical and complex than in centralized clouds. The goal of this thesis is to present new VM placement algorithms to optimize cost and carbon emission in a distributed cloud. It first focuses on cost efficiency in distributed clouds and, then, extends the goal to optimization of both cost and carbon emission at the same time. Thesis includes two main parts. The first part of thesis proposes, develops and evaluates static VM placement algorithms to reach the mentioned goal where an initial placement of a VM holds throughout the lifetime of the VM. The second part proposes dynamic VM placement algorithms where the initial placement of VMs is allowed to change (e.g., through VM migration and consolidation). The first contribution is a survey of the state of the art on cost and carbon emission resource allocation in distributed cloud environments. The second contribution targets the challenge of optimizing inter-DC communication cost for large-scale tasks and proposes a Network-Aware Cost-Efficient Resource allocation method, called NACER, for distributed clouds. The goal is to minimize the network communication cost of running a task in a distributed cloud by selecting the DCs to provision the VMs in such a way that the total network distance (hop count or any reasonable measure) among the selected DCs is minimized. The third contribution proposes a Network-Aware Cost Efficient VM Placement method (called NACEV) for Distributed Clouds. NACEV is an extended version of NACER. While NACER only considers inter-DC communication cost, NACEV optimizes both communication and computing cost at the same time and also proposes a mapping algorithm to place VMs on Physical Machines (PMs) inside of the selected DCs. NACEV also considers some aspects such as heterogeneity of VMs, PMs and switches, variety of energy prices, multiple paths between PMs, effects of workload on cost (energy consumption) of cloud devices (i.e., switches and PMs) and also heterogeneity of energy model of cloud elements. The forth contribution presents a Cost and Carbon Emission-Efficient VM Placement Method (called CACEV) for green distributed clouds. CACEV is an extended version of NACEV. In addition to cost efficiency, CACEV considers carbon emission efficiency and green distributed clouds. It is a VM placement algorithm for joint optimization of computing and network resources, which also considers price, location and carbon emission rate of resources. It also, unlike previous contributions of thesis, considers IaaS Service Level Agreement (SLA) violation in the system model. To get a better performance, the fifth contribution proposes a dynamic Cost and Carbon Emission-Efficient VM Placement method (D-CACEV) for green distributed clouds. D-CACEV is an extended version of our previous work, CACEV, with additional figures, description and also live VM migration mechanisms. We show that our joint VM placement-reallocation mechanism can constantly optimize both cost and carbon emission at the same time in a distributed cloud
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VALLERO, GRETA. "Green Mobile Networks: from 4G to 5G and Beyond." Doctoral thesis, Politecnico di Torino, 2022. http://hdl.handle.net/11583/2960753.
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Ahvar, Ehsan. "Cost-efficient resource allocation for green distributed clouds." Electronic Thesis or Diss., Evry, Institut national des télécommunications, 2017. http://www.theses.fr/2017TELE0001.
Full textAbstract:
L'objectif de cette thèse est de présenter de nouveaux algorithmes de placement de machines virtuelles (VMs) à fin d’optimiser le coût et les émissions de carbone dans les Clouds distribués. La thèse se concentre d’abord sur la rentabilité des Clouds distribués, et développe ensuite les raisons d’optimiser les coûts ainsi que les émissions de carbone. La thèse comprend deux principales parties: la première propose, développe et évalue les algorithmes de placement statiques de VMs (où un premier placement d'une VM détient pendant toute la durée de vie de la VM). La deuxième partie propose des algorithmes de placement dynamiques de VMs où le placement initial de VM peut changer dynamiquement (par exemple, grâce à la migration de VMs et à leur consolidation). Cette thèse comprend cinq contributions. La première contribution est une étude de l'état de l'art sur la répartition des coûts et des émissions de carbone dans les environnements de clouds distribués. La deuxième contribution propose une méthode d'allocation des ressources, appelée NACER, pour les clouds distribués. L'objectif est de minimiser le coût de communication du réseau pour exécuter une tâche dans un cloud distribué. La troisième contribution propose une méthode de placement VM (appelée NACEV) pour les clouds distribués. NACEV est une version étendue de NACER. Tandis que NACER considère seulement le coût de communication parmi les DCs, NACEV optimise en même temps les coûts de communication et de calcul. Il propose également un algorithme de cartographie pour placer des machines virtuelles sur des machines physiques (PM). La quatrième contribution présente une méthode de placement VM efficace en termes de coûts et de carbone (appelée CACEV) pour les clouds distribués verts. CACEV est une version étendue de NACEV. En plus de la rentabilité, CACEV considère l'efficacité des émissions de carbone pour les clouds distribués. Pour obtenir une meilleure performance, la cinquième contribution propose une méthode dynamique de placement VM (D-CACEV) pour les clouds distribués. D-CACEV est une version étendue de notre travail précédent, CACEV, avec des chiffres supplémentaires, une description et également des mécanismes de migration de VM en direct. Nous montrons que notre mécanisme conjoint de réallocation-placement de VM peut constamment optimiser à la fois le coût et l'émission de carbone dans un cloud distribuéVirtual machine (VM) placement (i.e., resource allocation) method has a direct effect on both cost and carbon emission. Considering the geographic distribution of data centers (DCs), there are a variety of resources, energy prices and carbon emission rates to consider in a distributed cloud, which makes the placement of VMs for cost and carbon efficiency even more critical and complex than in centralized clouds. The goal of this thesis is to present new VM placement algorithms to optimize cost and carbon emission in a distributed cloud. It first focuses on cost efficiency in distributed clouds and, then, extends the goal to optimization of both cost and carbon emission at the same time. Thesis includes two main parts. The first part of thesis proposes, develops and evaluates static VM placement algorithms to reach the mentioned goal where an initial placement of a VM holds throughout the lifetime of the VM. The second part proposes dynamic VM placement algorithms where the initial placement of VMs is allowed to change (e.g., through VM migration and consolidation). The first contribution is a survey of the state of the art on cost and carbon emission resource allocation in distributed cloud environments. The second contribution targets the challenge of optimizing inter-DC communication cost for large-scale tasks and proposes a Network-Aware Cost-Efficient Resource allocation method, called NACER, for distributed clouds. The goal is to minimize the network communication cost of running a task in a distributed cloud by selecting the DCs to provision the VMs in such a way that the total network distance (hop count or any reasonable measure) among the selected DCs is minimized. The third contribution proposes a Network-Aware Cost Efficient VM Placement method (called NACEV) for Distributed Clouds. NACEV is an extended version of NACER. While NACER only considers inter-DC communication cost, NACEV optimizes both communication and computing cost at the same time and also proposes a mapping algorithm to place VMs on Physical Machines (PMs) inside of the selected DCs. NACEV also considers some aspects such as heterogeneity of VMs, PMs and switches, variety of energy prices, multiple paths between PMs, effects of workload on cost (energy consumption) of cloud devices (i.e., switches and PMs) and also heterogeneity of energy model of cloud elements. The forth contribution presents a Cost and Carbon Emission-Efficient VM Placement Method (called CACEV) for green distributed clouds. CACEV is an extended version of NACEV. In addition to cost efficiency, CACEV considers carbon emission efficiency and green distributed clouds. It is a VM placement algorithm for joint optimization of computing and network resources, which also considers price, location and carbon emission rate of resources. It also, unlike previous contributions of thesis, considers IaaS Service Level Agreement (SLA) violation in the system model. To get a better performance, the fifth contribution proposes a dynamic Cost and Carbon Emission-Efficient VM Placement method (D-CACEV) for green distributed clouds. D-CACEV is an extended version of our previous work, CACEV, with additional figures, description and also live VM migration mechanisms. We show that our joint VM placement-reallocation mechanism can constantly optimize both cost and carbon emission at the same time in a distributed cloud
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Cao, Fei. "Efficient Scientific Workflow Scheduling in Cloud Environment." OpenSIUC, 2014. https://opensiuc.lib.siu.edu/dissertations/802.
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Cloud computing enables the delivery of remote computing, software and storage services through web browsers following pay-as-you-go model. In addition to successful commercial applications, many research efforts including DOE Magellan Cloud project focus on discovering the opportunities and challenges arising from the computing and data-intensive scientific applications that are not well addressed by the current supercomputers, Linux clusters and Grid technologies. The elastic resource provision, noninterfering resource sharing and flexible customized configuration provided by the Cloud infrastructure has shed light on efficient execution of many scientific applications modeled as Directed Acyclic Graph (DAG) structured workflows to enforce the intricate dependency among a large number of different processing tasks. Meanwhile, the Cloud environment poses various challenges. Cloud providers and Cloud users pursue different goals. Providers aim to maximize profit by achieving higher resource utilization and users want to minimize expenses while meeting their performance requirements. Moreover, due to the expanding Cloud services and emerging newer technologies, the ever-increasing heterogeneity of the Cloud environment complicates the challenges for both parties. In this thesis, we address the workflow scheduling problem from different applications and various objectives. For batch applications, due to the increasing deployment of many data centers and computer servers around the globe escalated by the higher electricity price, the energy cost on running the computing, communication and cooling together with the amount of CO2 emissions have skyrocketed. In order to maintain sustainable Cloud computing facing with ever-increasing problem complexity and big data size in the next decades, we design and develop energy-aware scientific workflow scheduling algorithm to minimize energy consumption and CO2 emission while still satisfying certain Quality of Service (QoS) such as response time specified in Service Level Agreement (SLA). Furthermore, the underlying Cloud hardware/Virtual Machine (VM) resource availability is time-dependent because of the dual operation modes namely on-demand and reservation instances at various Cloud data centers. We also apply techniques such as Dynamic Voltage and Frequency Scaling (DVFS) and DNS scheme to further reduce energy consumption within acceptable performance bounds. Our multiple-step resource provision and allocation algorithm achieves the response time requirement in the step of forward task scheduling and minimizes the VM overhead for reduced energy consumption and higher resource utilization rate in the backward task scheduling step. We also evaluate the candidacy of multiple data centers from the energy and performance efficiency perspectives as different data centers have various energy and cost related parameters. For streaming applications, we formulate scheduling problems with two different objectives, namely one is to maximize the throughput under a budget constraint while another is to minimize execution cost under a minimum throughput constraint. Two different algorithms named as Budget constrained RATE (B-RATE) and Budget constrained SWAP (B-SWAP) are designed under the first objective; Another two algorithms, namely Throughput constrained RATE (TP-RATE) and Throughput constrained SWAP (TP-SWAP) are developed under the second objective.
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Balouek-Thomert, Daniel. "Scheduling on Clouds considering energy consumption and performance trade-offs : from modelization to industrial applications." Thesis, Lyon, 2016. http://www.theses.fr/2016LYSEN058/document.
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L'utilisation massive des services connectés dans les entreprises et les foyers a conduit à un développement majeur des "Ciouds" ou informatique en nuage. Les Clouds s'imposent maintenant comme un modèle économique attractif où le client paye pour utiliser des ressources ou des services à la demande sans avoir à se préoccuper de la maintenance ou du coût réel de l'infrastructure. Ce développement rencontre cependant un obstacle majeur du point de vue des fournisseurs de ce type d'architecture : la consommation électrique des moteurs du cloud, les "datacenters" ou centre de données.Cette thèse s'intéresse à l'efficacité énergétique des Clouds en proposant un framework d'ordonnancement extensible et multi-critères dans le but d'augmenter le rendement d'une infrastructure hétérogène d'un point de vue énergétique. Nous proposons une approche basée sur un curseur capable d'aggréger les préférences de l'opérateur et du client pour la création de politiques d'ordonnancement. L'enjeu est de dimensionner au plus juste le nombre de serveurs et composants actifs tout en respectant les contraintes d'exploitation, et ainsi réduire les impacts environnementaux liés à une consommation superflue.Ces travaux ont été validés de façon expérimentale sur la plateforme Grid'SOOO par leur intégration au sein de l'intergiciel DIET et font l'objet d'un transfert industriel au sein de la plateforme NUVEA que nous proposons. Cette plate-forme fournit un accompagnement pour l'opérateur et l'utilisateur allant de l'audit à l'optimisation des infrastructuresModern society relies heavily on the use of computational resources. Over the last decades, the number of connected users and deviees has dramatically increased, leading to the consideration of decentralized on-demand computing as a utility, commonly named "The Cloud". Numerous fields of application such as High Performance Computing (HPC). medical research, movie rendering , industrial facto ry processes or smart city management , benefit from recent advances of on-demand computation .The maturity of Cloud technologies led to a democratization and to an explosion of connected services for companies, researchers, techies and even mere mortals, using those resources in a pay-per-use fashion.ln particular, since the Cloud Computing paradigm has since been adopted in companies . A significant reason is that the hardware running the cloud andprocessing the data does not reside at a company physical site, which means thatthe company does not have to build computer rooms (known as CAPEX, CAPitalEXpenditures) or buy equipment, nor to fill and mainta in that equipment over a normal life-cycle (known as OPEX, Operational EXpenditures).This thesis revolves around the energy efficiency of Cloud platforms by proposing an extensible and multi-criteria framework, which intends to improve the efficiency of an heterogeneous platform from an energy consumption perspective. We propose an approach based on user involvement using the notion of a cursor offering the ability to aggregate cloud operator and end user preferences to establish scheduling policies . The objective is the right sizing of active servers and computing equipments while considering exploitation constraints, thus reducing the environmental impactassociated to energy wastage.This research work has been validated on experiments and simulations on the Grid'SOOO platform, the biggest shared network in Europe dedicated to research.lt has been integrated to the DIET middleware, and a industrial valorisation has beendone in the NUVEA commercial platform, designed during this thesis . This platform constitutes an audit and optimization tool of large scale infrastructures for operatorsand end users
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Lakshminarayanan, Srivathsan. "Nature Inspired Grey Wolf Optimizer Algorithm for Minimizing Operating Cost in Green Smart Home." University of Toledo / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1438102173.
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Horner, Nathaniel Charles. "Powering the Information Age: Metrics, Social Cost Optimization Strategies, and Indirect Effects Related to Data Center Energy Use." Research Showcase @ CMU, 2016. http://repository.cmu.edu/dissertations/696.
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This dissertation contains three studies examining aspects of energy use by data centers and other information and communication technology (ICT) infrastructure necessary to support the electronic services that now form such a pervasive aspect of daily life. The energy consumption of ICT in general and data centers in particular has been of growing interest to both industry and the public, with continued calls for increased efficiency and greater focus on environmental impacts. The first study examines the metrics used to assess data center energy performance and finds that power usage effectiveness (PUE), the de facto industry standard, only accounts for one of four critical aspects of data center energy performance. PUE measures the overhead of the facility infrastructure but does not consider the efficiency of the IT equipment, its utilization, or the emissions profile of the power source. As a result, PUE corresponds poorly with energy and carbon efficiency, as demonstrated using a small set of empirical data center energy use measurements. The second study lays out a taxonomy of indirect energy impacts to help assess whether ICT’s direct energy consumption is offset by its energy benefits, and concludes that ICT likely has a large potential net energy benefit, but that there is no consensus on the sign or magnitude of actual savings, which are largely dependent upon implementation details. The third study estimates the potential of dynamic load shifting in a content distribution network to reduce both private costs and emissions-related externalities associated with electricity consumption. Utilizing variable marginal retail prices based on wholesale electricity markets and marginal damages estimated from emissions data in a cost-minimization model, the analysis finds that load shifting can either reduce data center power bills by approximately 25%–33% or avoid 30%–40% of public damages, while a range of joint cost minimization strategies enables simultaneous reduction of both private and public costs. The vast majority of these savings can be achieved even under existing bandwidth and network distance constraints, although current industry trends towards virtualization, energy efficiency, and green powermay make load shifting less appealing.
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Le, Trung. "Towards Sustainable Cloud Computing: Reducing Electricity Cost and Carbon Footprint for Cloud Data Centers through Geographical and Temporal Shifting of Workloads." Thèse, Université d'Ottawa / University of Ottawa, 2012. http://hdl.handle.net/10393/23082.
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Cloud Computing presents a novel way for businesses to procure their IT needs. Its elasticity and on-demand provisioning enables a shift from capital expenditures to operating expenses, giving businesses the technological agility they need to respond to an ever-changing marketplace. The rapid adoption of Cloud Computing, however, poses a unique challenge to Cloud providers—their already very large electricity bill and carbon footprint will get larger as they expand; managing both costs is therefore essential to their growth.
This thesis squarely addresses the above challenge. Recognizing the presence of Cloud data centers in multiple locations and the differences in electricity price and emission intensity among these locations and over time, we develop an optimization framework that couples workload distribution with time-varying signals on electricity price and emission intensity for financial and environmental benefits. The framework is comprised of an optimization model, an aggregate cost function, and 6 scheduling heuristics.
To evaluate cost savings, we run simulations with 5 data centers located across North America over a period of 81 days. We use historical data on electricity price, emission intensity, and workload collected from market operators and research data archives. We find that our framework can produce substantial cost savings, especially when workloads are distributed both geographically and temporally—up to 53.35% on electricity cost, or 29.13% on carbon cost, or 51.44% on electricity cost and 13.14% on carbon cost simultaneously.
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Hasan, MD Sabbir. "Smart management of renewable energy in clouds : from infrastructure to application." Thesis, Rennes, INSA, 2017. http://www.theses.fr/2017ISAR0010/document.
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Avec l'avènement des technologies de Cloud computing et son adoption, les entreprises et les institutions académiques transfèrent de plus en plus leurs calculs et leurs données vers le Cloud. Alors que ce progrès et ce modèle simple d'accès ont eu un impact considérable sur notre communauté scientifique et industrielle en termes de réduction de la complexité et augmentation des revenus, les centres de données consomment énormément d'énergie, ce qui se traduit par des émissions plus élevées de C02. En réponse, de nombreux travaux de recherche se sont focalisés sur les enjeux du développement durable pour le Cloud à travers la réduction de la consommation d'énergie en concevant des stratégies d'efficacité énergétiques. Cependant, l'efficacité énergétique dans l'infrastructure du C!oud ne suffira pas à stimuler la réduction de • l'empreinte carbone. Il est donc impératif d'envisager une utilisation intelligente de l'énergie verte à la fois au niveau de l'infrastructure et de l'application pour réduire davantage l'empreinte carbone. Depuis peu, certains fournisseurs de Cloud computing alimentent leurs centres de données avec de l'énergie renouvelable. Les sources d'énergie renouvelable sont très intermittentes, ce qui crée plusieurs défis pour les gérer efficacement. Pour surmonter ces défis, nous étudions les options pour intégrer les différentes sources d'énergie renouvelable de manière réaliste et proposer un Cloud energy broker qui peut ajuster la disponibilité et la combinaison de prix pour acheter de l'énergie verte dynamiquement sur le marché de l'énergie et rendre les centres de données partiellement verts. Puis, nous introduisons le concept de la virtualisation de l'énergie verte, qui peut être vu comme une alternative au stockage d'énergie utilisé dans les centres de données pour éliminer le problème d'intermittence dans une certaine mesure. Avec l'adoption du concept de virtualisation, nous maximisons l'utilisation de l'énergie verte contrairement au stockage d'énergie qui induit des pertes d'énergie, tout en introduisant des Green SLA basé sur l'énergie verte pour le fournisseur de services et les utilisateurs finaux. En utilisant des traces réalistes et une simulation et une analyse approfondie, nous montrons que la proposition peut fournir un système efficace, robuste et rentable de gestion de l'énergie pour le centre de données. Si une gestion efficace de l'énergie en présence d'énergie verte intermittente est nécessaire, la façon dont les applications Cloud modernes peuvent tirer profit de la présence ou l'absence d'énergie verte n'a pas été suffisamment étudiée. Contrairement aux applications Batch, les applications Interactive Cloud doivent toujours être accessibles et ne peuvent pas être programmées à l'avance pour correspondre au profil d'énergie verte. Par conséquent, cette thèse propose une solution d'autoscaling adaptée à l'énergie pour exploiter les caractéristiques internes des applications et créer une conscience d'énergie verte dans l'application, tout en respectant les propriétés traditionnelles de QoS. Pour cela, nous concevons un contrôleur d'application green qui profite de la disponibilité de l'énergie verte pour effectuer une adaptation opportuniste dans une application gérée par un contrôleur orienté performance. L'expérience est réalisée avec une application réelle sur Grid5000 et les résultats montrent une réduction significative de la consommation d'énergie par rapport à l'approche orientée performance, tout en respectant les attributs traditionnels de QoSWith the advent of cloud enabling technologies and adoption of cloud computing, enterprise and academic institutions are moving their IT workload to the cloud. Although this prolific advancement and easy to access model have greatly impacted our scientific and industrial community in terms of reducing complexity and increasing revenue, data centers are consuming enormous amount of energy, which translates into higher carbon emission. In response, varieties of research work have focused on environmental sustainability for Cloud Computing paradigm through energy consumption reduction by devising energy efficient strategies. However, energy efficiency in cloud infrastructure alone is not going to be enough to boost carbon footprint reduction. Therefore, it is imperative to envision of smartly using green energy at infrastructure and application level for further reduction of carbon footprint. In recent years, some cloud providers are powering their data centers with renewable energy. The characteristics of renewable energy sources are highly intermittent which creates several challenges to manage them efficiently. To overcome the problem, we investigate the options and challenges to integrate different renewable energy sources in a realistic way and propose a Cloud energy broker, which can adjust the availability and price combination to buy Green energy dynamically from the energy market in advance to make a data center partially green. Later, we introduce the concept of Virtualization of Green Energy, which can be seen as an alternative to energy storage used in data center to eliminate the intermittency problem to some extent. With the adoption of virtualization concept, we maximize the usage of green energy contrary to energy storage which induces energy losses, while introduce Green Service Level Agreement based on green energy for service provider and end users. By •using realistic traces and extensive simulation and analysis, we show that, the proposal can provide an efficient, robust and cost-effective energy management scheme for data center. While an efficient energy management in the presence of intermittent green energy is necessary, how modern Cloud applications can take advantage of the presence/absence of green energy has not been studied with requisite effort. Unlike Batch applications, Interactive Cloud applications have to be always accessible and car not be scheduled in advance to match with green energy profile. Therefore, this thesis proposes an energy adaptive autoscaling solution to exploit applications internal to create green energy awareness in the application, while respecting traditional QoS properties. To elaborate, we design green energy aware application controller that takes advantage of green energy availability to perform opportunistic adaptation in an application along with performance aware application controller. Experiment is performed with real life application at Grid5000 and results show significant reduction of energy consumption while respecting traditional QoS attributes compared to performance aware approach
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Tsafack, Chetsa Ghislain Landry. "System Profiling and Green Capabilities for Large Scale and Distributed Infrastructures." Phd thesis, Ecole normale supérieure de lyon - ENS LYON, 2013. http://tel.archives-ouvertes.fr/tel-00946583.
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Nowadays, reducing the energy consumption of large scale and distributed infrastructures has truly become a challenge for both industry and academia. This is corroborated by the many efforts aiming to reduce the energy consumption of those systems. Initiatives for reducing the energy consumption of large scale and distributed infrastructures can without loss of generality be broken into hardware and software initiatives.Unlike their hardware counterpart, software solutions to the energy reduction problem in large scale and distributed infrastructures hardly result in real deployments. At the one hand, this can be justified by the fact that they are application oriented. At the other hand, their failure can be attributed to their complex nature which often requires vast technical knowledge behind proposed solutions and/or thorough understanding of applications at hand. This restricts their use to a limited number of experts, because users usually lack adequate skills. In addition, although subsystems including the memory are becoming more and more power hungry, current software energy reduction techniques fail to take them into account. This thesis proposes a methodology for reducing the energy consumption of large scale and distributed infrastructures. Broken into three steps known as (i) phase identification, (ii) phase characterization, and (iii) phase identification and system reconfiguration; our methodology abstracts away from any individual applications as it focuses on the infrastructure, which it analyses the runtime behaviour and takes reconfiguration decisions accordingly.The proposed methodology is implemented and evaluated in high performance computing (HPC) clusters of varied sizes through a Multi-Resource Energy Efficient Framework (MREEF). MREEF implements the proposed energy reduction methodology so as to leave users with the choice of implementing their own system reconfiguration decisions depending on their needs. Experimental results show that our methodology reduces the energy consumption of the overall infrastructure of up to 24% with less than 7% performance degradation. By taking into account all subsystems, our experiments demonstrate that the energy reduction problem in large scale and distributed infrastructures can benefit from more than "the traditional" processor frequency scaling. Experiments in clusters of varied sizes demonstrate that MREEF and therefore our methodology can easily be extended to a large number of energy aware clusters. The extension of MREEF to virtualized environments like cloud shows that the proposed methodology goes beyond HPC systems and can be used in many other computing environments.
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Oppenheim, Brian Michael. "Reducing Cluster Power Consumption by Dynamically Suspending Idle Nodes." DigitalCommons@CalPoly, 2010. https://digitalcommons.calpoly.edu/theses/305.
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Close to 1% of the world's electricity is consumed by computer servers. Given that the increased use of electricity raises costs and damages the environment, optimizing the world's computing infrastructure for power consumption is worthwhile. This thesis is one attempt at such an optimization. In particular, I began by building a cluster of 6 Intel Atom based low-power nodes to perform work analogous to data center clusters. Then, I installed a version of Hadoop modified with a novel power management system on the cluster. The power management system uses different algorithms to determine when to turn off idle nodes in the cluster.
Using the experimental cluster running a modified Hadoop installation, I performed a series of experiments. These tests assessed various strategies for choosing nodes to suspend across a variety of workloads. The experiments validated that turning off idle nodes can yield power savings. While my experimental procedure caused the apparent throughput to significantly decrease, I argue that using more realistic workloads would have yielded much better throughput with slightly reduced power consumption. Additionally, my analysis of the results, show that the percentage power savings in a larger, more realistically sized cluster would be higher than shown in my experiments.
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Hrabčak, Miroslav. "Informační strategie firmy." Master's thesis, Vysoké učení technické v Brně. Fakulta podnikatelská, 2011. http://www.nusl.cz/ntk/nusl-223080.
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Master´s thesis is focused on a presentation of entrepreneurial intention of corporate information strategy. The corporate information strategy is based on the analysis of current situation of the company and its environment which uses modern trends in IT business. It is about a complex solution which should help to the growth of turnover, strengthen of mark of company and stabilize the market position.
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Aken, Andrew. "How an Organization's Environmental Orientation Impacts Environmental Performance and its Resultant Financial Performance through Green Computing Hiring Practices: An Empirical Investigation of the Natural Resource-Based View of the Firm." OpenSIUC, 2010. https://opensiuc.lib.siu.edu/dissertations/194.
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This dissertation uses the logic embodied in Strategic Fit Theory, the Natural Resource-Based View of the Firm (NRBV), strategic human resource management, and other relevant literature streams to empirically demonstrate how the environmental orientation of a firm's strategy impacts their environmental performance and resultant financial performance through the firm's Information Technology hiring practices. Specifically, it was hypothesized that firms with a strong relationship between the environmental orientation of their strategy and their green computing hiring practices will achieve higher environmental performance, and, as a result, higher levels of financial performance than firms lacking such fit. The organization's environmental orientation was measured via content analysis of the annual report texts (ARTs). Environmental performance was measured using KLD's award-winning environmental performance metrics. I triangulated across efficiency, effectiveness, and market-based metrics to capture a more holistic measure of the firm's financial performance using data from Compustat/Research Insight. The firm's green computing hiring practices were measured utilizing a web content data mining application that pulled job ads for computing graduates and then extracted the environmentally-oriented skills identified in such ads using content analytic techniques. Various control variables were employed to eliminate possible alternative explanations of my research findings. A number of statistical and analytical techniques were used to assess the nature and strength of the relationships in my theoretical model as are articulated in the proposed hypotheses. The sample size of firms is fairly large, thus increasing the statistical power of the empirical tests. Previous empirical testing of the relationship between environmental strategy and financial performance is still in the developmental stages and has produced mixed results, partly because important intervening mechanisms, such as green computing hiring practices, has not received adequate attention in the empirical literature. The combination of using a large sample of real world firms, a powerful combination of qualitative and quantitative methodological techniques to tap into key trace evidence not available through other methodological techniques, and leveraging an award-winning environmental data set has enhanced the robustness of the empirical findings in addressing this important gap in the literature. The results of the analyses show that there is a strong relationship between an organization's environmental posturing and its environmental performance. Additionally, this effect is mediated by the organization's environmental hiring practices, indicating that implementing the organization's environmental strategy through its hiring practices is important in achieving improved environmental performance. The current research also shows that there is a strong and positive relationship between an organization's environmental performance and financial performance. Surprisingly, these relationships are not significantly impacted by the organization's industry affiliation, which broadens the generalizability of the results of this study.
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Cirqueira, Alexandre Correia. "Um Mecanismo de SeguranÃa com AdaptaÃÃo DinÃmica em Tempo de ExecuÃÃo para Dispositivos MÃveis." Universidade Federal do CearÃ, 2011. http://www.teses.ufc.br/tde_busca/arquivo.php?codArquivo=7165.
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CoordenaÃÃo de AperfeiÃoamento de Pessoal de NÃvel SuperiorA crescente utilizaÃÃo de dispositivos mÃveis, redes sem fio e aplicaÃÃes mÃveis evidencia a importÃncia da garantia de seguranÃa da informaÃÃo. Esta preocupaÃÃo surge devido aos riscos envolvidos no trÃfego de informaÃÃes sensÃveis por meio sem fio, uma vez que o meio nÃo limita os riscos de ataques, tal como nas redes convencionais. Adicionalmente, a tendÃncia no uso de prÃticas sustentÃveis defendidas pela ComputaÃÃo Verde impÃe a necessidade de concepÃÃo de aplicaÃÃes flexÃveis que busquem a reduÃÃo do consumo de recursos, como o de energia. Assim, mecanismos para o provimento de confidencialidade de informaÃÃes que trafegam por meio sem fio devem considerar a alocaÃÃo eficiente de recursos computacionais. Esta à uma questÃo chave a ser considerada no momento da concepÃÃo de aplicaÃÃes mÃveis seguras. Portanto, os mecanismos de proteÃÃo devem balancear o nÃvel de seguranÃa requerido de acordo com o consumo de recursos alocados para provÃ-lo. O emprego de informaÃÃes que caracterizam a situaÃÃo corrente (contexto) pode auxiliar nessa tarefa. Assim, a utilizaÃÃo de proteÃÃo adequada aos requisitos de seguranÃa das aplicaÃÃes e combinada com o contexto pode identificar situaÃÃes nas quais serà necessÃrio aumentar ou diminuir o nÃvel de seguranÃa, de forma a diminuir o consumo de recursos do dispositivo. Esse trabalho propÃe, portanto, um Mecanismo de SeguranÃa com AdaptaÃÃo DinÃmica (MeSAD), com foco na confidencialidade, capaz de adaptar o nÃvel de seguranÃa de acordo com o contexto e reduzir o consumo de recursos dos dispositivos mÃveis. O objetivo principal consiste em encontrar o ponto de equilÃbrio no tradeoff entre nÃvel de seguranÃa e consumo de recursos. A fim de atingir este objetivo, este trabalho apresenta tambÃm uma ferramenta de suporte à utilizaÃÃo do MeSAD durante o desenvolvimento de aplicaÃÃes mÃveis, alÃm de possibilitar a realizaÃÃo de avaliaÃÃes sobre o desempenho dos algoritmos criptogrÃficos que sÃo utilizados nos diferentes dispositivos.
The increasing use of mobile devices, wireless networks and mobile applications highlights the importance of ensuring information security. This concern arises because of the risks involved in traffic sensitive information via wireless, since it does not limit the risk of attacks, as in conventional networks. Additionally, the trend in the use of sustainable practices advocated by the Green Computing imposes the need for designing flexible applications that seek to reduce consumption of resources such as energy. Thus, mechanisms for providing confidentiality of information passing over the wireless medium should consider the efficient allocation of computing resources. This is a key issue to be considered when designing secure mobile applications. Therefore, the protection mechanisms should balance the security level required in accordance with the consumption of resources allocated to provide it. The use of information that characterizes the current situation (context) can assist in this task. Thus, the use of appropriate protective security requirements of applications and combined with the context can identify situations where you need to raise or lower the security level in order to reduce the resource consumption of the device. This work proposes a Security Mechanism Dynamic Adaptation (MeSAD), focusing on confidentiality, able to adapt the level of security according to the context and reduce the resource consumption of mobile devices. The main objective is to find the balance point in the tradeoff between the level of security and resource consumption. In order to achieve this goal, this paper presents a tool to support the use of MeSAD during the development of mobile applications, and enable the assessments on the performance of cryptographic algorithms that are used in different devices.
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Gilman, Ekaterina, Anja Keskinarkaus, Satu Tamminen, Susanna Pirttikangas, Juha Röning, and Jukka Riekki. "Personalised assistance for fuel-efficient driving." Elsevier, 2015. https://publish.fid-move.qucosa.de/id/qucosa%3A72830.
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Recent advances in technology are changing the way how everyday activities are performed. Technologies in the traffic domain provide diverse instruments of gathering and analysing data for more fuel-efficient, safe, and convenient travelling for both drivers and passengers. In this article, we propose a reference architecture for a context-aware driving assistant system. Moreover, we exemplify this architecture with a real prototype of a driving assistance system called Driving coach. This prototype collects, fuses and analyses diverse information, like digital map, weather, traffic situation, as well as vehicle information to provide drivers in-depth information regarding their previous trip along with personalised hints to improve their fuel-efficient driving in the future. The Driving coach system monitors its own performance, as well as driver feedback to correct itself to serve the driver more appropriately.
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MORAES, Renato Ubaldo Moreira e. "SSACC -SERVIÇO DE SEGURANÇA PARA AUTENTICAÇÃO CIENTE DO CONTEXTO: para Dispositivos Móveis no Paradigma da Computação em Nuvem." Universidade Federal do Maranhão, 2014. http://tedebc.ufma.br:8080/jspui/handle/tede/291.
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Nowadays, there was a massive inclusion of smart mobile devices, known as smartphones, and with this accession, there s consequently a large increase in the consumption of information, especially from the internet. To support the great demand for information access, it s created a numerous devices to facilitate both access, the creation and the storage of such information, among the best known and disseminated currently is cloud computing. The feedback takes currently, an increasingly important and even critical for some entities, size and value turns out to be very desirable. Being often target capture and espionage attempts. To obtain data confidential information hackers use numerous devices, and more is used to scan networks. In other words can be described as scan "Scans notifications in computer networks, in order to identify which computers are active and which services are available for them. It is widely used by attackers to identify potential targets because it allows associate potential vulnerabilities to services enabled on a computer " [10]. According to [10] the number of attacks has been widening each year as shown in Figure 1.1 and 1.2 which are in section 1.1. Based on this high number incidents, the growth of the information consumer by means of devices furniture and the need to improve energy costs, the proposed establishment of the Office Security for Context Aware of authentication (Serviço de Segurança para Autenticação Ciente do Contexto(SSACC)) is required for today. The ssacc focus to provide a secure channel for transfer files to a server, using context information and reducing energy waste, thus saving resources and framing the Green Computing. Made based on the Secure Socket Layer (SSL), which is a widely used protocol that provides secure communication through a network. It uses several different cryptographic processes to ensure that data sent through the network is secure. It provides a security enhancement for the Transport Control Protocol (TCP) / Internet Protocol (IP) standard, which is used for communication with the Internet. SSL uses public key cryptography to provide authentication. The SSL protocol also uses encryption of the private key and digital signatures to ensure privacy and the integrity of data " [26].
Atualmente houve uma adesão em massa aos dispositivos móveis inteligentes, conhecidos como smartphones, e, com essa adesão, houve consequentemente um grande aumento no consumo da informação, principalmente proveniente da internet. Para atender a grande demanda de acesso à informação foi criado inúmeros artifícios para facilitar tanto o acesso, quanto a criação e o armazenamento dessas informações, dentre os mais conhecidos e difundidos atualmente está a computação em nuvem. A informação assume, hoje em dia, uma importância crescente e até vital para algumas entidades, e com tamanho valor acaba se tornando muito desejada, sendo muitas vezes alvo de tentativas de captura e espionagem. Para se obter dados de informações confidenciais hackers usam inúmeros artifícios, e o mais usado é o scan de redes, que em outras palavras pode ser descrito scan como "notificações de varreduras em redes de computadores, com o intuito de identificar quais computadores estão ativos e quais serviços estão sendo disponibilizados por eles. É amplamente utilizado por atacantes para identificar potenciais alvos, pois permite associar possíveis vulnerabilidades aos serviços habilitados em um computador" [10]. De acordo com o [10] o número de ataques só vem crescendo a cada ano como mostra a figura 1.1 e 1.2 que estão na seção 1.1. Com base nesse alto número de incidentes, o crescimento do consumo da informação por meio de dispositivos móveis e a necessidade de melhorar gastos de energia, a proposta de criação do Serviço de Segurança para Autenticação Ciente do Contexto (SSACC) é necessária para a atualidade. O SSACC tem como principal objetivo fornecer um canal seguro para transferência de arquivos para um servidor, fazendo uso de informações de contexto e diminuindo o desperdício de energia, consequentemente economizando recursos e se enquadrando à Computação Verde. Feito com base no Secure Socket Layer(SSL), que é um "protocolo amplamente utilizado que fornece comunicação segura através de uma rede. Ele usa vários processos criptográficos diferentes para garantir que os dados enviados por meio de rede são seguras. Ele fornece um aprimoramento de segurança para o protocolo Transport Control Protocol (TCP)/ Internet Protocol (IP) padrão, que é usado para comunicação com a internet. SSL utiliza criptografia de chave pública para fornecer autenticação. O protocolo SSL também usa criptografia de chave privada e assinaturas digitais para garantir a privacidade e a integridade dos dados" [26].
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Frisk, Arfvidsson Nils, and David Östlin. "Green Cloud Transition & Environmental Impacts of Stock Exchanges : A Case Study of Nasdaq, a Global Stock Exchange Company." Thesis, KTH, Skolan för industriell teknik och management (ITM), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-279615.
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To address the issues of climate change and reduce the emissions released into the atmosphere, society and companies, including the financial markets, need to adjust how they act and conduct business. The financial markets are vital in the transition towards a more sustainable society and stock exchanges are a central actor to enhance green finance, enabling green securities to be traded. For stock exchange companies to stand tall and encourage a green transition, they need to be aware of their own internal environmental impact. As society is changing to become more serviceoriented, so is stock exchanges. A part of enabling servitization is the usage of cloud services which not only enable companies to focus more on their core business, it also has the potential to reduce companies’ environmental footprint. This study examines the environmental impact of a stock exchange company and how it can be reduced by transitioning to cloud computing. The study uses Nasdaq as a case company and examines environmental performance data from major stock exchanges worldwide. The study furthermore uses the Multi-Level Perspective (MLP) to understand what enables and disables a cloud transition for stock exchanges. This study concludes that the main environmental impact of a stock exchange is Business Travel, electricity and heat for Office Buildings and Data Centres, although the order of these varies throughout the industry. Further, it is concluded that a stock exchange can reduce its environmental footprint by transitioning to cloud computing, in the best-case scenario, emissions are reduced with 10 percent and electricity usage reduced with almost 30 percent of the total usage. However, the impact of a transition is dependent on the rate of renewable energy used for the data centre. The study finds that a cloud transition includes enablers and disablers on all three levels on the MLP and it will most likely be incremental innovations together with a business model shift and technical traits of cloud that will enable and open the window of opportunity for a regime shift. It is concluded that technology or IT-security of cloud computing is not hindering a cloud transition, rather it is organizational culture, assumptions, financial lock-ins, and landscape protectionism that are disablers for a transition. To overcome those, and reduce the environmental footprint, stock exchanges need to work together with cloud providers to create use cases that are in line with the regulatory and financial requirements of a stock exchange.För att hantera klimatförändringar och reducera utsläppen i atmosfären måste samhället och företag, inklusive de finansiella marknaderna anpassa hur de agerar och bedriver verksamhet. De finansiella marknaderna är vitala för övergången till ett mer hållbart samhälle och börser är en central aktör för att utveckla grön finans och möjliggöra handel av gröna värdepapper. Om börsbolag ska stå rakryggade och uppmuntra till en grön övergång måste de vara medvetna om deras egen interna miljöpåverkan. I takt med att samhället förändras till att bli mer serviceinriktat, förändras också börserna. En faktor för att möjliggöra servitisering är användningen av molntjänster, som inte bara möjliggör mer fokus på kärnverksamhet utan har också potential att minska företags miljöpåverkan. Denna studie undersöker miljöeffekterna av ett börsföretag och hur det kan minskas genom en övergång till molntjänster. Studien använder Nasdaq som ett caseföretag samt undersöker data om miljöpåverkan från de stora börserna världen över. Vidare, för att förstå vad som möjliggör och förhindrar en molnövergång för börser använder studien Multi-Level Perspective (MLP). De viktigaste resultaten från denna studie är att den största miljöpåverkan av en börs är affärsresor, el och värme för kontorsbyggnader samt datacenter, dock varierar ordningen på dessa mellan börser. Studien konkluderar att en börs kan minska deras miljöpåverkan genom att övergå till molntjänster, i bästa fall kan molntjänster minska utsläppen med 10 procent och minska elanvändningen med nästan 30 procent av den totala användningen. Effekterna av en övergång är dock mycket beroende av andelen förnybar energi som användas av de olika datacentren. Studien konstaterar flertalet faktorer på alla tre nivåer av MLP som både möjliggör och förhindrar en molnövergång. Det kommer sannolikt vara inkrementellinnovation tillsammans med affärsmodellsförändringar och tekniska egenskaper för molntjänster som möjliggör och öppnar fönstret till regimskifte. Studien konkluderar att det inte är tekniken eller IT-säkerheten för molntjänster som förhindrar en molnövergång utan det är organisationskulturen, förutfattade meningar, ekonomiska inlåsningar och landskapsprotektionism som förhindrar en molnövergång. För att övervinna dessa och minska miljöpåverkan måste börserna samarbeta med molntjänsteleverantörer för att skapa use cases som är i linje med lagstiftningen och de finansiella kraven på en börs.
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Cheik, Ahamed Abal-Kassim. "Méthodes numériques pour la résolution accélérée des systèmes linéaires de grandes tailles sur architectures hybrides massivement parallèles." Thesis, Châtenay-Malabry, Ecole centrale de Paris, 2015. http://www.theses.fr/2015ECAP0035.
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Les progrès en termes de puissance de calcul ont entraîné de nombreuses évolutions dans le domaine de la science et de ses applications. La résolution de systèmes linéaires survient fréquemment dans le calcul scientifique, comme par exemple lors de la résolution d'équations aux dérivées partielles par la méthode des éléments finis. Le temps de résolution découle alors directement des performances des opérations algébriques mises en jeu.Cette thèse a pour but de développer des algorithmes parallèles innovants pour la résolution de systèmes linéaires creux de grandes tailles. Nous étudions et proposons comment calculer efficacement les opérations d'algèbre linéaire sur plateformes de calcul multi-coeur hétérogènes-GPU afin d'optimiser et de rendre robuste la résolution de ces systèmes. Nous proposons de nouvelles techniques d'accélération basées sur la distribution automatique (auto-tuning) des threads sur la grille GPU suivant les caractéristiques du problème et le niveau d'équipement de la carte graphique, ainsi que les ressources disponibles. Les expérimentations numériques effectuées sur un large spectre de matrices issues de divers problèmes scientifiques, ont clairement montré l'intérêt de l'utilisation de la technologie GPU, et sa robustesse comparée aux bibliothèques existantes comme Cusp.L'objectif principal de l'utilisation du GPU est d'accélérer la résolution d'un problème dans un environnement parallèle multi-coeur, c'est-à-dire "Combien de temps faut-il pour résoudre le problème?". Dans cette thèse, nous nous sommes également intéressés à une autre question concernant la consommation énergétique, c'est-à-dire "Quelle quantité d'énergie est consommée par l'application?". Pour répondre à cette seconde question, un protocole expérimental est établi pour mesurer la consommation d'énergie d'un GPU avec précision pour les opérations fondamentales d'algèbre linéaire. Cette méthodologie favorise une "nouvelle vision du calcul haute performance" et apporte des réponses à certaines questions rencontrées dans l'informatique verte ("green computing") lorsque l'on s'intéresse à l'utilisation de processeurs graphiques.Le reste de cette thèse est consacré aux algorithmes itératifs synchrones et asynchrones pour résoudre ces problèmes dans un contexte de calcul hétérogène multi-coeur-GPU. Nous avons mis en application et analysé ces algorithmes à l'aide des méthodes itératives basées sur les techniques de sous-structurations. Dans notre étude, nous présentons les modèles mathématiques et les résultats de convergence des algorithmes synchrones et asynchrones. La démonstration de la convergence asynchrone des méthodes de sous-structurations est présentée. Ensuite, nous analysons ces méthodes dans un contexte hybride multi-coeur-GPU, qui devrait ouvrir la voie vers les méthodes hybrides exaflopiques.Enfin, nous modifions la méthode de Schwarz sans recouvrement pour l'accélérer à l'aide des processeurs graphiques. La mise en oeuvre repose sur l'accélération par les GPUs de la résolution locale des sous-systèmes linéaires associés à chaque sous-domaine. Pour améliorer les performances de la méthode de Schwarz, nous avons utilisé des conditions d'interfaces optimisées obtenues par une technique stochastique basée sur la stratégie CMA-ES (Covariance Matrix Adaptation Evolution Strategy). Les résultats numériques attestent des bonnes performances, de la robustesse et de la précision des algorithmes synchrones et asynchrones pour résoudre de grands systèmes linéaires creux dans un environnement de calcul hétérogène multi-coeur-GPUAdvances in computational power have led to many developments in science and its applications. Solving linear systems occurs frequently in scientific computing, as in the finite element discretization of partial differential equations. The running time of the overall resolution is a direct result of the performance of the involved algebraic operations.In this dissertation, different ways of efficiently solving large and sparse linear systems are put forward. We present the best way to effectively compute linear algebra operations in an heterogeneous multi-core-GPU environment in order to make solvers such as iterative methods more robust and therefore reduce the computing time of these systems. We propose new techniques to speed algorithms up the auto-tuning of the threading design, according to the problem characteristics and the equipment level in the hardware and available resources. Numerical experiments performed on a set of large-size sparse matrices arising from diverse engineering and scientific problems, have clearly shown the benefit of the use of GPU technology to solve large sparse systems of linear equations, and its robustness and accuracy compared to existing libraries such as Cusp.The main priority of the GPU program is computational time to obtain the solution in a parallel environment, i.e, "How much time is needed to solve the problem?". In this thesis, we also address another question regarding energy issues, i.e., "How much energy is consumed by the application?". To answer this question, an experimental protocol is established to measure the energy consumption of a GPU for fundamental linear algebra operations accurately. This methodology fosters a "new vision of high-performance computing" and answers some of the questions outlined in green computing when using GPUs.The remainder of this thesis is devoted to synchronous and asynchronous iterative algorithms for solving linear systems in the context of a multi-core-GPU system. We have implemented and analyzed these algorithms using iterative methods based on sub-structuring techniques. Mathematical models and convergence results of synchronous and asynchronous algorithms are presented here, as are the convergence results of the asynchronous sub-structuring methods. We then analyze these methods in the context of a hybrid multi-core-GPU, which should pave the way for exascale hybrid methods.Lastly, we modify the non-overlapping Schwarz method to accelerate it, using GPUs. The implementation is based on the acceleration of the local solutions of the linear sub-systems associated with each sub-domain using GPUs. To ensure good performance, optimized conditions obtained by a stochastic technique based on the Covariance Matrix Adaptation Evolution Strategy (CMA-ES) are used. Numerical results illustrate the good performance, robustness and accuracy of synchronous and asynchronous algorithms to solve large sparse linear systems in the context of an heterogeneous multi-core-GPU system
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Raphael, Pedro Luis Furio. "Escalonamento de tarefas em processadores de velocidade variável em múltiplas organizações." Universidade de São Paulo, 2015. http://www.teses.usp.br/teses/disponiveis/45/45134/tde-25062015-161751/.
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Problemas de escalonamento cuja função objetivo é o consumo de energia tem sido cada vez mais estudados. Neste trabalho, estudamos o problema conhecido, em inglês, por Dynamic Speed Scaling, um problema de escalonamento de tarefas bem definidas em processadores de velocidade variável, cujo consumo de energia é função da velocidade. Além disso, relacionamos este problema com outro conhecido como MOSP, sigla em inglês para Multi-Organization Scheduling Problem. Neste, queremos escalonar tarefas de múltiplas organizações independentes respeitando certas restrições individuais. Provamos, neste trabalho, que este novo problema é NP-Completo e desenvolvemos várias heurísticas eficientes cujos testes experimentais mostram economia de energia significativa.We studied, in this work, the problem of scheduling a set of well-defined tasks in a variable speed processor with the objective of minimizing the energy consumption, that is given as a function of the processor\'s speed, field known as Dynamic Speed Scaling. Also, we relate this problem to another known as MOSP (Multi-Organization Scheduling Problem), problem in which several independent organizations share tasks and resources to achieve a better global solution, but also respecting selfish restrictions. For the combined problem, we show that it is NP-Complete and designed several efficient heuristics that achieves good results in a experimental setup.
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Östlin, David, and Arfvidsson Nils Frisk. "Green Cloud Transition & Environmental Impacts of Stock Exchanges : A Case Study of Nasdaq, a Global Stock Exchange Company." Thesis, KTH, Industriell ekonomi och organisation (Inst.), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-278173.
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To address the issues of climate change and reduce the emissions released into the atmosphere, society and companies, including the financial markets, need to adjust how they act and conduct business. The financial markets are vital in the transition towards a more sustainable society and stock exchanges are a central actor to enhance green finance, enabling green securities to be traded. For stock exchange companies to stand tall and encourage a green transition, they need to be aware of their own internal environmental impact. As society is changing to become more service-oriented, so is stock exchanges. A part of enabling servitization is the usage of cloud services which not only enable companies to focus more on their core business, it also has the potential to reduce companies’ environmental footprint. This study examines the environmental impact of a stock exchange company and how it can be reduced by transitioning to cloud computing. The study uses Nasdaq as a case company and examines environmental performance data from major stock exchanges worldwide. The study furthermore uses the Multi-Level Perspective (MLP) to understand what enables and disables a cloud transition for stock exchanges. This study concludes that the main environmental impact of a stock exchange is Business Travel, electricity and heat for Office Buildings and Data Centres, although the order of these varies throughout the industry. Further, it is concluded that a stock exchange can reduce its environmental footprint by transitioning to cloud computing, in the best-case scenario, emissions are reduced with 10 percent and electricity usage reduced with almost 30 percent of the total usage. However, the impact of a transition is dependent on the rate of renewable energy used for the data centre. The study finds that a cloud transition includes enablers and disablers on all three levels on the MLP and it will most likely be incremental innovations together with a business model shift and technical traits of cloud that will enable and open the window of opportunity for a regime shift. It is concluded that technology or IT-security of cloud computing is not hindering a cloud transition, rather it is organizational culture, assumptions, financial lock-ins, and landscape protectionism that are disablers for a transition. To overcome those, and reduce the environmental footprint, stock exchanges need to work together with cloud providers to create use cases that are in line with the regulatory and financial requirements of a stock exchange.För att hantera klimatförändringar och reducera utsläppen i atmosfären måste samhället och företag, inklusive de finansiella marknaderna anpassa hur de agerar och bedriver verksamhet. De finansiella marknaderna är vitala för övergången till ett mer hållbart samhälle och börser är en central aktör för att utveckla grön finans och möjliggöra handel av gröna värdepapper. Om börsbolag ska stå rakryggade och uppmuntra till en grön övergång måste de vara medvetna om deras egen interna miljöpåverkan. I takt med att samhället förändras till att bli mer serviceinriktat, förändras också börserna. En faktor för att möjliggöra servitisering är användningen av molntjänster, som inte bara möjliggör mer fokus på kärnverksamhet utan har också potential att minska företags miljöpåverkan. Denna studie undersöker miljöeffekterna av ett börsföretag och hur det kan minskas genom en övergång till molntjänster. Studien använder Nasdaq som ett caseföretag samt undersöker data om miljöpåverkan från de stora börserna världen över. Vidare, för att förstå vad som möjliggör och förhindrar en molnövergång för börser använder studien Multi-Level Perspective (MLP). De viktigaste resultaten från denna studie är att den största miljöpåverkan av en börs är affärsresor, el och värme för kontorsbyggnader samt datacenter, dock varierar ordningen på dessa mellan börser. Studien konkluderar att en börs kan minska deras miljöpåverkan genom att övergå till molntjänster, i bästa fall kan molntjänster minska utsläppen med 10 procent och minska elanvändningen med nästan 30 procent av den totala användningen. Effekterna av en övergång är dock mycket beroende av andelen förnybar energi som användas av de olika datacentren. Studien konstaterar flertalet faktorer på alla tre nivåer av MLP som både möjliggör och förhindrar en molnövergång. Det kommer sannolikt vara inkrementellinnovation tillsammans med affärsmodellsförändringar och tekniska egenskaper för molntjänster som möjliggör och öppnar fönstret till regimskifte. Studien konkluderar att det inte är tekniken eller IT-säkerheten för molntjänster som förhindrar en molnövergång utan det är organisationskulturen, förutfattade meningar, ekonomiska inlåsningar och landskapsprotektionism som förhindrar en molnövergång. För att övervinna dessa och minska miljöpåverkan måste börserna samarbeta med molntjänsteleverantörer för att skapa use cases som är i linje med lagstiftningen och de finansiella kraven på en börs.
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Honée, Caspar. "Environmental Performance of the Försäkringskassan IT Infrastructure : A Green-IT case study for the Swedish Social Insurance Agency." Thesis, Mittuniversitetet, Avdelningen för ekoteknik och hållbart byggande, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-20003.
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This Green IT case study commissioned by Försäkringskassan (FK), the Swedish National Social Insurance Agency, quantifies the environmental performance of the IT infrastructure (IT-IS) in use during 2010 in a lifecycle perspective. Adopting a system view in Green IT analysis can mitigate risks of problem shifts. IT-IS concerns the equipment that enables office automation and external web application services. The size of the FK IT-IS is in the order of 300 branch offices with 14000 pc’s, 2100 printers and a 1 MW data centre hosting 1200 servers, 5 Petabyte of central data storage and serving about 80 key business applications. The carbon footprint of the FK IT-IS in 2010 accounts to 6.5 kiloton CO2-equivalents. The total environmental impact is calculated across 18 themes and expressed as a single indicator eco score amounting to 822.000 ReCiPe points. The contribution of capital goods is large with 44% of the carbon footprint and 47% of the eco score linked to emissions embedded in material equipment. The environmental effects from distributed IT deployed at local office sites, dominate at two thirds of the total FK IT-IS impacts. Important drivers in the local office sites category are the relatively short economic life span of pc equipment and the significant volume of paper consumed in printing activities. Within the data centre category, operational processes dominate the environmental impacts and are linked to intensive power use. In comparison to industry benchmark scores, the data centre infrastructure energy efficiency (DCiE) is relatively low at 57%, or 59% when credited for waste heat utilisation. Airflow containment measures in computer rooms are identified for efficiency improvement. Enhanced airflow controls also act as a prerequisite to better leverage opportunities for free cooling present at the location in northern Europe. With regards to the data centre hosted IT, environmental impacts linked to storage services dominate and remarkably exceed those of servers.Denna fallstudie inom Grön IT på uppdrag av Försäkringskassan (FK) kvantifierar IT-infrastrukturens (IT-IS) miljöprestanda i ett livscykelperspektiv under 2010. Att införa ett systemperspektiv inom Grön IT analys kan lindra riskerna av problemväxling. IT-IS avser utrustning som möjliggör kontorsautomatisering och externa webbapplikationer. FK IT-IS omfattar 300 kontor med 14,000 datorer, 2,100 skrivare och ett 1 MW datacenter med 1,200 servrar, 5 Petabyte central datalagring och 80 huvudsakliga applikationer. Koldioxidavtrycket av det totala FK IT-IS utgör 6,5 kiloton CO2-ekvivalenter för 2010 . Den totala miljöpåverkan är beräknad över 18 miljöteman och anger som en enda indikator ekobetyget på 822,000 ReCiPe poäng . Kapitalvaror bidrar stort, med hela 44% av koldioxidutsläppen och 47% av ekobetyget kan härledas till inbäddade utsläpp i material utrustning. Miljöeffekterna av de lokala kontorens IT dominerar med två tredjedelar av den totala FK IT-IS miljöpåverkan. Viktiga faktorer i kategorin lokala kontor är kapitalvarornas relativt korta ekonomiska livslängd samt de betydande volymer av skrivarpapper som används. Inom datacenterkategorin domineras miljöpåverkan av de operativa processerna som är kopplade till intensiv el förbrukning. I jämförelse med branschstandarden är energieffektiviteten av datacentrets infrastruktur (DCiE) relativt låg, med 57%, alternativt 59% när användandet av spillvärme inräknas. Luftflöde inneslutningsåtgärder i datorsalar identifieras för effektivisering. Förbättrad luftflödesinneslutning i datahallarna är identifierad som en energieffektivisering. Den förbättrade luftflödeskontrollen är också ett krav för att bättre kunna utnyttja möjligheterna för fri kyla som finns i Norra Europa. Med avseende på datacentrets IT, domineras miljökonsekvenserna kopplade till lagringstjänster och överstiger anmärkningsvärt effekterna från servrarna.
Miljöutredning Grön IT på Försäkringskassan - examensarbeten
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Santos, André Ramalho dos. "Sintonizador termoelétrico assistido por férmions de Majorana." Universidade Estadual Paulista (UNESP), 2017. http://hdl.handle.net/11449/152726.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
Nós estudamos teoricamente como o calor e a eletricidade são afetados pela sobreposição de dois férmions de Majorana (MFs, de Majorana fermions em Inglês), os quais estão isolados nas bordas de um fio topológico de Kitaev, em particular, na forma de “ferradura”. É considerado que esse fio está assimetricamente acoplado a um único ponto quântico (QD, de Quantum dot em Inglês) hibridizado com contatos metálicos. Em baixas temperaturas e dependente do nível de energia desse QD, nós mostramos que ao ajustar a assimetria acima, as respostas ressonantes das condutâncias termoelétricas mudam inesperadamente de forma drástica. Assim, propomos como aplicação, um sintonizador termoelétrico em nanoescala assistido por MFs.
We study theoretically in a topological U-shaped Kitaev wire, with Majorana fermions (MFs) on the edges, how heat and electricity are affected by them when found overlapped. The asymmetric regime of their couplings with a single quantum dot (QD) hybridized with metallic leads is considered. At low temperatures and dependent upon the QD energy level, we show that by tuning this asymmetry, the resonance positions of the thermoelectrical conductances change drastically. Thereby, the tuner of heat and electricity here proposed is constituted.
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Peres, Martin. "A holistic approach to green networking in wireless networks : collaboration among autonomic systems as a mean towards efficient resource-sharing." Thesis, Bordeaux, 2014. http://www.theses.fr/2014BORD0433/document.
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Les vingt dernières années ont vu l’émergence de systèmes sans fil dans la vie de tous les jours. Ils ont rendu possible la création de technologies telles que les téléphones portables, le WiFi ou l’internet mobile qui sont maintenant tenus pour acquis dans la société actuelle. L’impact environnemental des technologies de l’information et des communications connaît une croissance exponentielle et a atteint l’impact de l’industrie du transport aérien. L’initiative d’informatique verte a été lancée en réponse à cette observation pour réduire de 15 à 30% les émissions de gaz à effet de serre en 2020 comparé aux prédictions faites en 2002 afin de garder le réchauffement climatique inférieur à 2°C. Dans cette thèse, nous avons étudié des techniques d’économie d’énergie dans les réseaux sans fil et comment elles interagissent entre elles afin de donner une vue holistique des réseaux verts. Nous prenons également en compte l’usage du spectre radio fréquence qui est le moyen le plus utilisé pour les communications entre systèmes sans fil et qui devient une ressource rare à cause du besoin grandissant de notre société pour de la bande passante en mobilité. Cette thèse suit les couches réseaux avant de remonter les piles matérielleset logicielles. Des contributions ont été apportées à la plupart des couches afin de proposer un réseau sans fil autonome où les noeuds peuvent collaborer pour améliorer les performances du réseau, réduire de façon globale l’utilisation du spectre radio tout en limitant la consommation énergétique du réseauThe last twenty years saw the emergence of wireless systems in everyday’s life. They made possible technologies such as mobile phones, WiFi or mobile Internet which are now taken for granted in today’s society. The environmental impact of Information and Communications Technology (ICT) has been raising exponentially to equate the impact of the airline industry. The green computing initiative has been created in response to this observation in order to meet the 15%-30% reduction in green-house gases by 2020 compared to estimations made in 2002 to keep the global temperature increasebelow 2°C. In this thesis, we studied power-saving techniques in wireless networks and how they interact with each others to provide a holistic view of green networking. We also take into account the radio frequency resource which is the most commonly usedcommunication medium for wireless systems and is becoming a scarce resource due to our society’s ever-increasing need for mobile bandwidth. This thesis goes down the network stacks before going up the hardware and software stack. Contributions have been madeat most layers in order to propose an autonomic wireless network where nodes can work collaboratively to improve the network’s performance, globally reduce the radio frequency spectrum usage while also increasing their battery life
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Borges, caldas da silva Pedro Victor. "Middleware support for energy awareness in the Internet of Things (IoT)." Electronic Thesis or Diss., Institut polytechnique de Paris, 2022. http://www.theses.fr/2022IPPAS016.
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L'Internet des objets (IoT) se caractérise par une myriade de dispositifs et de composants logiciels géographiquement dispersés ainsi que par une grande hétérogénéité en termes de matériel, de format de données et de protocoles. Au cours des dernières années, les plateformes IoT ont été proposées pour fournir une variété de services aux applications, tels que la découverte de dispositifs, la gestion du contexte et l'analyse des données. Cependant, le manque de standardisation fait que chaque plateforme IoT propose ses propres abstractions, API et patrons d'interactions. Par conséquent, la programmation des interactions entre une application IoT consommatrice de données et une plateforme IoT est complexe, sujette à des erreurs et demande un niveau de connaissance de la plateforme IoT approfondi de la part des développeurs. Les intergiciels IoT peuvent atténuer cette hétérogénéité, ils doivent fournir des services pertinents et ainsi faciliter le développement des applications.L'efficacité énergétique de la technologie numérique devenant une priorité, l'augmentation du nombre de systèmes IoT pose des problèmes énergétiques. Dans ce contexte, il est essentiel de concevoir soigneusement les interactions entre les applications IoT grand public et les plateformes IoT en tenant compte de l'efficacité énergétique. Les intergiciels IoT ne doivent pas uniquement considérer l'efficacité énergétique comme une exigence non fonctionnelle laissée à l'application, Au contraire, parce qu'ils sont utilisés par de nombreuses applications, l'efficacité énergétique doit être au cœur de leur conception.Cette thèse présente trois contributions concernant l'efficacité énergétique et la sensibilisation à l'énergie dans les intergiciels IoT pour les applications IoT consommatrices de données. La première contribution est la proposition d'un intergiciel IoT appelé IoTvar qui abstrait les capteurs virtuels IoT dans des variables IoT qui sont automatiquement mises à jour par l'intergiciel. La deuxième contribution est l'évaluation de la consommation d'énergie des interactions entre les applications IoT grand public et les plateformes IoT via les protocoles HTTP et MQTT. Cette évaluation a conduit à la proposition de lignes directrices pour améliorer l'efficacité énergétique des interactions. La troisième contribution est la proposition de stratégies d'efficacité énergétique pour des middleware IoT. Ces stratégies ont été intégrées dans l'intergiciel IoTvar pour assurer l'efficacité énergétique, mais aussi la sensibilisation à l'énergie par le biais d'un modèle énergétique et la gestion d'un budget énergétique fonction des exigences des utilisateurs. Les implémentations de l'architecture middleware IoT, avec et sans stratégie d'efficacité énergétique, ont été évaluées, et les résultats montrent que nous avons une diminution allant jusqu'à 60% de l'énergie consommée par les applications IoT en appliquant des stratégies pour réduire la consommation d'énergie au niveau du middlewareThe Internet of Things (IoT) is characterized by a myriad of geographically dispersed devices and software components as well as high heterogeneity in terms of hardware, data, and protocols. Over the last few years, IoT platforms have been used to provide a variety of services to applications such as device discovery, context management, and data analysis. However, the lack of standardization makes each IoT platform come with its abstractions, APIs, and interactions. As a consequence, programming the interactions between a consuming IoT application and an IoT platform is often time-consuming, error-prone, and depends on the developers' level of knowledge about the IoT platform. IoT middleware are proposed to alleviate such heterogeneity, provide relevant services, and ease application development.As the energy efficiency of digital technology becomes a priority, the increase in IoT systems brings energy concerns. In this context, carefully designing interactions between IoT consumer applications and IoT systems with an energy-efficiency concern becomes essential. IoT middleware should not solely consider energy efficiency as a non-functional requirement. Instead, it needs to be at the solution's core as the middleware is expected to be shared by many applications and offer facilities to ease application development.This work presents three contributions regarding energy-efficiency/awareness in IoT middleware for IoT consumer applications.The first contribution is the proposal of an IoT middleware for IoT consumer applications called IoTVar that abstracts IoT virtual sensors in IoT variables that are automatically updated by the middleware.The second contribution is the evaluation of the energy consumption of the interactions between IoT consumer applications and IoT platforms through the HTTP and MQTT protocols. This evaluation has led to the proposal of guidelines to improve energy efficiency when developing applications.The third contribution is the proposal of strategies for energy efficiency to be integrated into IoT middleware. Those strategies have been integrated into the IoTVar middleware to provide energy efficiency, but also energy awareness through an energy model and the management of an energy budget driven by user requirements. The implementations of the IoT middleware architecture, with and without energy-efficiency strategies, have been evaluated, and the results show that we have a difference of up to 60% the energy used by IoT applications by applying strategies to reduce energy consumption at the middleware level
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Nergis, Damirag Melodi. "Web Based Cloud Interaction and Visualization of Air Pollution Data." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-254401.
Full textAbstract:
According to World Health Organization, around 7 million people die every year due to diseases caused by air pollution. With the improvements in Internet of Things in the recent years, environmental sensing systems has started to gain importance. By using technologies like Cloud Computing, RFID, Wireless Sensor Networks, and open Application Programming Interfaces, it has become easier to collect data for visualization on different platforms. However, collected data need to be represented in an efficient way for better understanding and analysis, which requires design of data visualization tools. The GreenIoT initiative aims to provide open data with its infrastructure for sustainable city development in Uppsala. An environmental web application is presented within this thesis project, which visualizes the gathered environmental data to help municipality organizations to implement new policies for sustainable urban planning, and citizens to gain more knowledge to take sustainable decisions in their daily life. The application has been developed making use of the 4Dialog API, which is developed to provide data from a dedicated cloud storage for visualization purposes. According to the evaluation presented in this thesis, further development is needed to improve the performance to provide faster and more reliable service as well as the accessibility to promote openness and social inclusion.Enligt World Health Organization dör 7 miljoner människor varje år på grund av sjukdomar orsakade av luftföroreningar. Med förbättringar inom Internet of Things under senare år, har betydelsen av system för miljösensorer. Genom att använda tekniker som molntjänster, RFID, trådlösa sensornätverk och öppna programmeringsgränssnitt, har det blivit enklare att samla in data för visualisering på olika plattformar. Men insamlad data behöver bli representerad på ett effektivt sätt för bättre förståelse och analys, vilket kräver utformande av verktyg för visualisering av data. Initiativet GreenIoT strävar mot att erbjuda öppen data med sin infrastruktur för hållbar stadsutveckling i Uppsala. I detta arbete presenteras en webb-tillämpning, som visualiserar den insamlade miljödatan för att hjälpa kommunen att implementera nya policies för hållbar stadsutveckling, och stimulera medborgare till att skaffa mer kunskap för att göra miljövänliga val i sin vardag. Tillämpningen har utvecklats med hjälp av 4Dialog API, som tillhandahåller data från lagring i molnet för visualiseringssyfte. Enligt den utvärdering som presenteras i denna rapport konstateras att vidare utveckling behövs för att förbättra dels prestanda för att erbjuda en snabbare och mer tillförlitlig service, och dels åtkomstmöjligheter för att främja öppenhet och social inkludering.