Дисертації з теми "Cloud data centers"
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Mahmud, A. S. M. Hasan. "Sustainable Resource Management for Cloud Data Centers." FIU Digital Commons, 2016. http://digitalcommons.fiu.edu/etd/2634.
Повний текст джерелаJawad, Muhammad. "Energy Efficient Data Centers for On-Demand Cloud Services." Diss., North Dakota State University, 2015. http://hdl.handle.net/10365/25198.
Повний текст джерелаZhang, Gong. "Data and application migration in cloud based data centers --architectures and techniques." Diss., Georgia Institute of Technology, 2011. http://hdl.handle.net/1853/41078.
Повний текст джерелаPenumetsa, Swetha. "A comparison of energy efficient adaptation algorithms in cloud data centers." Thesis, Blekinge Tekniska Högskola, Institutionen för datalogi och datorsystemteknik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-17374.
Повний текст джерелаTakouna, Ibrahim. "Energy-efficient and performance-aware virtual machine management for cloud data centers." Phd thesis, Universität Potsdam, 2014. http://opus.kobv.de/ubp/texte_eingeschraenkt_verlag/2014/7239/.
Повний текст джерелаVirtualized cloud data centers provide on-demand resources, enable agile resource provisioning, and host heterogeneous applications with different resource requirements. These data centers consume enormous amounts of energy, increasing operational expenses, inducing high thermal inside data centers, and raising carbon dioxide emissions. The increase in energy consumption can result from ineffective resource management that causes inefficient resource utilization. This dissertation presents detailed models and novel techniques and algorithms for virtual resource management in cloud data centers. The proposed techniques take into account Service Level Agreements (SLAs) and workload heterogeneity in terms of memory access demand and communication patterns of web applications and High Performance Computing (HPC) applications. To evaluate our proposed techniques, we use simulation and real workload traces of web applications and HPC applications and compare our techniques against the other recently proposed techniques using several performance metrics. The major contributions of this dissertation are the following: proactive resource provisioning technique based on robust optimization to increase the hosts' availability for hosting new VMs while minimizing the idle energy consumption. Additionally, this technique mitigates undesirable changes in the power state of the hosts by which the hosts' reliability can be enhanced in avoiding failure during a power state change. The proposed technique exploits the range-based prediction algorithm for implementing robust optimization, taking into consideration the uncertainty of demand. An adaptive range-based prediction for predicting workload with high fluctuations in the short-term. The range prediction is implemented in two ways: standard deviation and median absolute deviation. The range is changed based on an adaptive confidence window to cope with the workload fluctuations. A robust VM consolidation for efficient energy and performance management to achieve equilibrium between energy and performance trade-offs. Our technique reduces the number of VM migrations compared to recently proposed techniques. This also contributes to a reduction in energy consumption by the network infrastructure. Additionally, our technique reduces SLA violations and the number of power state changes. A generic model for the network of a data center to simulate the communication delay and its impact on VM performance, as well as network energy consumption. In addition, a generic model for a memory-bus of a server, including latency and energy consumption models for different memory frequencies. This allows simulating the memory delay and its influence on VM performance, as well as memory energy consumption. Communication-aware and energy-efficient consolidation for parallel applications to enable the dynamic discovery of communication patterns and reschedule VMs using migration based on the determined communication patterns. A novel dynamic pattern discovery technique is implemented, based on signal processing of network utilization of VMs instead of using the information from the hosts' virtual switches or initiation from VMs. The result shows that our proposed approach reduces the network's average utilization, achieves energy savings due to reducing the number of active switches, and provides better VM performance compared to CPU-based placement. Memory-aware VM consolidation for independent VMs, which exploits the diversity of VMs' memory access to balance memory-bus utilization of hosts. The proposed technique, Memory-bus Load Balancing (MLB), reactively redistributes VMs according to their utilization of a memory-bus using VM migration to improve the performance of the overall system. Furthermore, Dynamic Voltage and Frequency Scaling (DVFS) of the memory and the proposed MLB technique are combined to achieve better energy savings.
Yanggratoke, Rerngvit. "Contributions to Performance Modeling and Management of Data Centers." Licentiate thesis, KTH, Kommunikationsnät, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-129296.
Повний текст джерелаQC 20131001
Peloso, Pietro. "Possibili soluzioni per garantire qos nelle comunicazioni inter-data centers in ambienti cloud computing." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2013. http://amslaurea.unibo.it/6205/.
Повний текст джерелаAtchukatla, Mahammad suhail. "Algorithms for efficient VM placement in data centers : Cloud Based Design and Performance Analysis." Thesis, Blekinge Tekniska Högskola, Institutionen för datalogi och datorsystemteknik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-17221.
Повний текст джерела- Perform simulation of algorithms in CloudSim simulator. Estimate and compare the energy consumption of different packing algorithms. Design an OpenStack testbed to implement the Bin packing algorithm. Methods: We use CloudSim simulator to estimate the energy consumption of the First fit, the First fit decreasing, Best fit and Enhanced best-fit algorithms. Design a heuristic model for implementation in the OpenStack environment for optimizing the energy consumption for the physical machines. Server consolidation and live migration are used for the algorithms design in the OpenStack implementation. Our research also extended to the Nova scheduler functionality in an OpenStack environment. Results: Most of the case the enhanced best-fit algorithm gives the better results. The results are obtained from the default OpenStack VM placement algorithm as well as from the heuristic algorithm developed in this simulation work. The comparison of results indicates that the total energy consumption of the data center is reduced without affecting potential service level agreements. Conclusions: The research tells that energy consumption of the physical machines can be optimized without compromising the offered service quality. A Python wrapper was developed to implement this model in the OpenStack environment and minimize the energy consumption of the Physical machine by shutdown the unused physical machines. The results indicate that CPU Utilization does not vary much when live migration of the virtual machine is performed.
Pipkin, Everest R. "It Was Raining in the Data Center." Research Showcase @ CMU, 2018. http://repository.cmu.edu/theses/138.
Повний текст джерелаBergström, Rasmus. "Predicting Container-Level Power Consumption in Data Centers using Machine Learning Approaches." Thesis, Luleå tekniska universitet, Institutionen för system- och rymdteknik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-79416.
Повний текст джерелаAlharbi, Fares Abdi H. "Profile-based virtual machine management for more energy-efficient data centers." Thesis, Queensland University of Technology, 2019. https://eprints.qut.edu.au/129871/8/Fares%20Abdi%20H%20Alharbi%20Thesis.pdf.
Повний текст джерелаLe, 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.
Повний текст джерелаWang, Chengwei. "Monitoring and analysis system for performance troubleshooting in data centers." Diss., Georgia Institute of Technology, 2013. http://hdl.handle.net/1853/50411.
Повний текст джерелаChkirbene, Zina. "Network topologies for cost reduction and QoS improvement in massive data centers." Thesis, Bourgogne Franche-Comté, 2017. http://www.theses.fr/2017UBFCK002/document.
Повний текст джерелаData centers (DC) are being built around the world to provide various cloud computing services. One of the fundamental challenges of existing DC is to design a network that interconnects massive number of nodes (servers)1 while reducing DC' cost and energy consumption. Several solutions have been proposed (e.g. FatTree, DCell and BCube), but they either scale too fast (i.e., double exponentially) or too slow. Effcient DC topologies should incorporate high scalability, low latency, low Average Path Length (APL), high Aggregated Bottleneck Throughput (ABT) and low cost and energy consumption. Therefore, in this dissertation, different solutions have been proposed to overcome these problems. First, we propose a novel DC topology called LCT (Linked Cluster Topology) as a new solution for building scalable and cost effective DC networking infrastructures. The proposed topology reduces the number of redundant connections between clusters of nodes, while increasing the numbers of nodes without affecting the network bisection bandwidth. Furthermore, in order to reduce the DCs cost and energy consumption, we propose first a new static energy saving topology called VacoNet (Variable Connection Network) that connects the needed number of servers while reducing the unused materials (cables, switches). Also, we propose a new approach that exploits the correlation in time of internode communication and some topological features to maximize energy saving without too much impacting the average path length
Soares, Maria José. "Data center - a importância de uma arquitectura." Master's thesis, Universidade de Évora, 2011. http://hdl.handle.net/10174/11604.
Повний текст джерелаRoozbeh, Amir. "Toward Next-generation Data Centers : Principles of Software-Defined “Hardware” Infrastructures and Resource Disaggregation." Licentiate thesis, KTH, Kommunikationssystem, CoS, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-249618.
Повний текст джерелаQC 20190415
Feller, Eugen. "Autonomic and Energy-Efficient Management of Large-Scale Virtualized Data Centers." Phd thesis, Université Rennes 1, 2012. http://tel.archives-ouvertes.fr/tel-00785090.
Повний текст джерелаWeerasinghe, Jagath [Verfasser], Andreas [Akademischer Betreuer] Herkersdorf, Christian [Gutachter] Plessl, and Andreas [Gutachter] Herkersdorf. "Standalone Disaggregated Reconfigurable Computing Platforms in Cloud Data Centers / Jagath Weerasinghe ; Gutachter: Christian Plessl, Andreas Herkersdorf ; Betreuer: Andreas Herkersdorf." München : Universitätsbibliothek der TU München, 2018. http://d-nb.info/1160381321/34.
Повний текст джерелаMadi, wamba Gilles. "Combiner la programmation par contraintes et l’apprentissage machine pour construire un modèle éco-énergétique pour petits et moyens data centers." Thesis, Ecole nationale supérieure Mines-Télécom Atlantique Bretagne Pays de la Loire, 2017. http://www.theses.fr/2017IMTA0045/document.
Повний текст джерелаOver the last decade, cloud computing technologies have considerably grown, this translates into a surge in data center power consumption. The magnitude of the problem has motivated numerous research studies around static or dynamic solutions to reduce the overall energy consumption of a data center. The aim of this thesis is to integrate renewable energy sources into dynamic energy optimization models in a data center. For this we use constraint programming as well as machine learning techniques. First, we propose a global constraint for tasks intersection that takes into account a ressource with variable cost. Second, we propose two learning models for the prediction of the work load of a data center and for the generation of such curves. Finally, we formalize the green energy aware scheduling problem (GEASP) and propose a global model based on constraint programming as well as a search heuristic to solve it efficiently. The proposed model integrates the various aspects inherent to the dynamic planning problem in a data center : heterogeneous physical machines, various application types (i.e., ractive applications and batch applications), actions and energetic costs of turning ON/OFF physical machine, interrupting/resuming batch applications, CPU and RAM ressource consumption of applications, migration of tasks and energy costs related to the migrations, prediction of green energy availability, variable energy consumption of physical machines
Dagala, Wadzani Jabani. "Analysis of Total Cost of Ownership for Medium Scale Cloud Service Provider with emphasis on Technology and Security." Thesis, Blekinge Tekniska Högskola, Institutionen för datalogi och datorsystemteknik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-15003.
Повний текст джерела
Furgiuele, Antonio. "Architecture of the cloud, virtualization takes command : learning from black boxes, data centers and an architecture of the conditioned environment." Thesis, Massachusetts Institute of Technology, 2013. http://hdl.handle.net/1721.1/81746.
Повний текст джерелаThis electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (p. 127-128).
A single manageable architecture of the Cloud has been one of the most important social and technical changes of the 21st century. Cloud computing, our newest public utility is an attempt to confront and control cultural risk, it has rendered the environment of our exchanges calculable, manageable, seemingly predictable, and most importantly as a new form of capital. Cloud computing in its most basic terms is the system of virtualization of data storage and program access into an instantaneous service utility. The transformation of computing into a service industry is one of the key changes of the Information Age, and its logic is tied to the highly guarded mechanisms of a black box, an architecture machine, or more commonly known as the data center. In 2008, on a day with without the usual fanfare or barrage of academic manifestoes, grand claims of paradigm shifts, virtualization quietly took command. A seemingly simple moment where a cloud, the Cloud, emerged as a new form of managerial space that tied a large system of users to the hidden mechanisms of large scaled factories of information, a network of data centers. The project positions the Cloud and the data center into the architectural discourse, both historically and materially, through an analysis of its relationship to an emergent digital sublime and how it is managed, controlled and propelled through the obscure typologies of its architecture and images. The study of the Cloud and the data center through the notion of the sublime, and the organizational structures of typology we can more critically assess architecture's relationship to this new phase of the Information Age.
by Antonio Furgiuele.
S.M.in History, Theory and Criticism of Art and Architecture
Ruty, Guillaume. "Towards more scalability and flexibility for distributed storage systems." Thesis, Université Paris-Saclay (ComUE), 2019. http://www.theses.fr/2019SACLT006/document.
Повний текст джерелаThe exponentially growing demand for storage puts a huge stress on traditionnal distributed storage systems. While storage devices' performance have caught up with network devices in the last decade, their capacity do not grow as fast as the rate of data growth, especially with the rise of cloud big data applications. Furthermore, the performance balance between storage, network and compute devices has shifted and the assumptions that are the foundation for most distributed storage systems are not true anymore. This dissertation explains how several aspects of such storage systems can be modified and rethought to make a more efficient use of the resource at their disposal. It presents an original architecture that uses a distributed layer of metadata to provide flexible and scalable object-level storage, then proposes a scheduling algorithm improving how a generic storage system handles concurrent requests. Finally, it describes how to improve legacy filesystem-level caching for erasure-code-based distributed storage systems, before presenting a few other contributions made in the context of short research projects
Rostirolla, Gustavo. "Ordonnancement dans un centre de calculs alimenté par des sources d'énergie renouvelables sans connexion au réseau avec une charge de travail mixte basée sur des phases." Thesis, Toulouse 3, 2019. http://www.theses.fr/2019TOU30160.
Повний текст джерелаDue to the increase of cloud, web-services and high performance computing demands all over the world, datacenters are now known to be one of the biggest actors when talking about energy consumption. In 2006 alone, datacenters were responsible for consuming 61.4 billion kWh in the United States. When looking at the global scenario, datacenters are currently consuming more energy than the entire United Kingdom, representing about 1.3\% of world's electricity consumption, and being even called the factories of the digital age. Supplying datacenters with clean-to-use renewable energy is therefore essential to help mitigate climate change. The vast majority of cloud provider companies that claim to use green energy supply on their datacenters consider the classical grid, and deploy the solar panels/wind turbines somewhere else and sell the energy to electricity companies, which incurs in energy losses when the electricity travels throughout the grid. Even though several efforts have been conducted at the computing level in datacenters partially powered by renewable energy sources, the scheduling considering on site renewable energy sources and its variations, without connection to the grid can still be widely explored. Since energy efficiency in datacenters is directly related to the resource consumption of the computing nodes, performance optimization and an efficient load scheduling are essential for energy saving. Today, we observe the use of cloud computing as the basis of datacenters, either in a public or private fashion. The main particularity of our approach is that we consider a power envelope composed only by renewable energy as a constraint, hence with a variable amount of power available at each moment. The scheduling under this kind of constraint becomes more complex: without further checks, we are not ensured that a running task will run until completion. We start by addressing the IT load scheduling of batch tasks, which are characterized by their release time, due date and resource demand, in a cloud datacenter while respecting the aforementioned power envelope. The data utilized for the batch tasks comes from datacenter traces, containing CPU, memory and network values. The power envelopes considered, represent an estimation which would be provided by a power decision module and is the expected power production based on weather forecasts. The aim is to maximize the Quality of Service with a variable constraint on electrical power. Furthermore, we explore a workload composed by batch and services, where the resources consumption varies over time. The traces utilized for the service tasks originate from business critical datacenter. In this case we rely on the concept of phases, where each significant resource change in the resources consumption constitutes a new phase of the given task. In this task model phases could also receive less resources than requested. The reduction of resources can impact the QoS and consequently the datacenter profit. In this approach we also include the concept of cross-correlation to evaluate where to place a task under a power curve, and what is the best node to place tasks together (i.e. sharing resources). Finally, considering the previous workload of batch tasks and services, we present an approach towards handling unexpected events in the datacenter. More specifically we focus on IT related events such as tasks arriving at any given time, demanding more or less resources than expected, or having a different finish time than what was initially expected. We adapt the proposed algorithms to take actions depending on which event occurs, e.g. task degradation to reduce the impact on the datacenter profit
Benblidia, Mohammed Anis. "Pour une meilleure efficacité énergétique dans un système Smart Grid - Cloud." Thesis, Troyes, 2021. http://www.theses.fr/2021TROY0019.
Повний текст джерелаThis thesis considers the energy efficiency of information and communication infrastructures in a smart grid - cloud system. It especially deals with communication networks and cloud data centers due to their high energy consumption, which confers them an important role in the network. The contributions of this thesis are implemented on the same framework integrating the smart grid, microgrid, cloud, data centers and users. Indeed, we have studied the interaction between the cloud data centers and the smart grid provider and we have proposed energy efficient power allocation solutions and an energy cost minimization scheme using two architectures: a smart grid-cloud architecture and a microgrid-cloud architecture. In addition, we paid close attention to execute user requests while ensuring a good quality of service in a fog-cloud architecture. In comparison with state-of-the-art works, the results of our contributions have shown that they respond to the identified challenges, particularly in terms of reducing carbon emissions and energy costs of cloud data centers
Božić, Nikola. "Blockchain technologies and their application to secure virtualized infrastructure control." Electronic Thesis or Diss., Sorbonne université, 2019. http://www.theses.fr/2019SORUS596.
Повний текст джерелаBlockchain is a technology making the shared registry concept from distributed systems a reality for a number of application domains, from the cryptocurrency one to potentially any industrial system requiring decentralized, robust, trusted and automated decision making in a multi-stakeholder situation. Nevertheless, the actual advantages in using blockchain instead of any other traditional solution (such as centralized databases) are not completely understood to date, or at least there is a strong need for a vademecum guiding designers toward the right decision about when to adopt blockchain or not, which kind of blockchain better meets use-case requirements, and how to use it. At first, we aim at providing the community with such a vademecum, while giving a general presentation of blockchain that goes beyond its usage in Bitcoin and surveying a selection of the vast literature that emerged in the last few years. We draw the key requirements and their evolution when passing from permissionless to permissioned blockchains, presenting the differences between proposed and experimented consensus mechanisms, and describing existing blockchain platforms. Furthermore, we present the B-VMOA blockchain to secure virtual machine orchestration operations for cloud computing and network functions virtualization systems applying the proposed vademecum logic. Using tutorial examples, we describe our design choices and draw implementation plans. We further develop the vademecum logic applied to cloud orchestration and how it can lead to precise platform specifications. We capture the key system operations and complex interactions between them. We focus on the last release of Hyperledger Fabric platform as a way to develop B-VMOA system. Besides, Hyperledger Fabric optimizes conceived B-VMOA network performance, security, and scalability by way of workload separation across: (i) transaction execution and validation peers, and (ii) transaction ordering nodes. We study and use a distributed execute-order-validate architecture which differentiates our conceived B-VMOA system from legacy distributed systems that follow a traditional state-machine replication architecture. We parameterize and validate our model with data collected from a realistic testbed, presenting an empirical study to characterize system performance and identify potential performance bottlenecks. Furthermore, we present the tools we used, the network setup and the discussion on empirical observations from the data collection. We examine the impact of various configurable parameters to conduct an in-dept study of core components and benchmark performance for common usage patterns. Namely, B-VMOA is meant to be run within data center. Different data center interconnection topologies scale differently due to communication protocols. Enormous challenges appear to efficiently design the network interconnections so that the deployment and maintenance of the infrastructure is cost-effective. We analyze the structural properties of several DCN topologies and also present some comparison among these network architectures with the aim to reduce B-VMOA overhead costs. From our analysis, we recommend the hypercube topology as a solution to address the performance bottleneck in the B-VMOA control plane caused by gossip dissemination protocol along with an estimate of performance improvement
Bayati, Léa. "Data centers energy optimization." Thesis, Paris Est, 2019. http://www.theses.fr/2019PESC0063.
Повний текст джерелаTo ensure both good data center service performance and reasonable power consumption, a detailed analysis of the behavior of these systems is essential for the design of efficient optimization algorithms to reduce energy consumption. This thesis fits into this context, and our main work is to design dynamic energy management systems based on stochastic models of controlled queues. The goal is to search for optimal control policies for data center management, which should meet the growing demands of reducing energy consumption and digital pollution while maintaining quality of service. We first focused on the modeling of dynamic energy management by a stochastic model for a homogeneous data center, mainly to study some structural properties of the optimal strategy, such as monotony. Afterwards, since data centers have a significant level of server heterogeneity in terms of energy consumption and service rates, we have generalized the homogeneous model to a heterogeneous model. In addition, since the data center server's wake-up and shutdown are not instantaneous and a server requires a little more time to go from sleep mode to ready-to-work mode, we have extended the model to the purpose of including this server time latency. Throughout this exact optimization, arrivals and service rates are specified with histograms that can be obtained from actual traces, empirical data, or traffic measurements. We have shown that the size of the MDP model is very large and leads to the problem of the explosion of state space and a large computation time. Thus, we have shown that optimal optimization requiring a MDP is often difficult or almost impossible to apply for large data centers. Especially if we take into account real aspects such as server heterogeneity or latency. So, we have suggested what we call the greedy-window algorithm that allows to find a sub-optimal strategy better than that produced when considering a special mechanism like threshold approaches. And more importantly, unlike the MDP approach, this algorithm does not require the complete construction of the structure that encodes all possible strategies. Thus, this algorithm gives a strategy very close to the optimal strategy with very low space-time complexities. This makes this solution practical, scalable, dynamic and can be put online
Sriram, Ilango Leonardo. "Exploration of scaling properties in cloud data centres." Thesis, University of Bristol, 2011. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.573405.
Повний текст джерелаSergejev, Ivan. "Exposing the Data Center." Thesis, Virginia Tech, 2014. http://hdl.handle.net/10919/51838.
Повний текст джерелаMaster of Architecture
Zhuang, Hao. "Performance Evaluation of Virtualization in Cloud Data Center." Thesis, KTH, Skolan för informations- och kommunikationsteknik (ICT), 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-104206.
Повний текст джерелаAmazon Elastic Compute Cloud (EC2) har antagits av ett stort antal små och medelstora företag (SMB), t.ex. foursquare, Monster World, och Netflix, för att ge olika typer av tjänster. Det finns en del tidigare arbeten i den aktuella litteraturen som undersöker variationen och oförutsägbarheten av molntjänster. Dessa arbetenhar visat intressanta iakttagelser om molnerbjudanden, men de har misslyckats med att avslöja den underliggande kärnan hos de olika utseendena för molntjänster. I denna avhandling tittade vi på de underliggande schemaläggningsmekanismerna och maskinvarukonfigurationer i Amazon EC2, och undersökte deras inverkan på resultatet för de virtuella maskiners instanser som körs ovanpå. Närmare bestämt är det flera fall med standard- och hög-CPU instanser som omfattas att belysa uppgradering av hårdvara och utbyte av Amazon EC2. Stora instanser från standardfamiljen är valda för att genomföra en fokusanalys. För att bättre förstå olika beteenden av de olika instanserna har lokala kluster miljöer inrättas, dessa klustermiljöer består av två Intel Xeonservrar och har inrättats med hjälp av olika schemaläggningsalgoritmer. Genom en serie benchmarkmätningar observerade vi följande slutsatser: (1) Amazon använder mycket diversifierad hårdvara för att tillhandahållandet olika instanser. Från de olika instans-sub-typernas perspektiv leder hårdvarumångfald till betydande prestationsvariation som kan nå upp till 30%. (2) Två olika schemaläggningsmekanismer observerades, en liknande Simple Earliest Deadline Fist(SEDF) schemaläggare, medan den andra mer liknar Credit-schemaläggaren i Xenhypervisor. Dessa två schemaläggningsmekanismer ger även upphov till variationer i prestanda. (3) Genom att tillämpa en enkel "trial-and-failure" strategi för val av instans, är kostnadsbesparande förvånansvärt stor. Med tanke på fördelning av snabba och långsamma instanser kan kostnadsbesparingen uppgå till 30%, vilket är attraktivt för små och medelstora företag som använder Amazon EC2 plattform.
Gao, Xing. "Investigating Emerging Security Threats in Clouds and Data Centers." W&M ScholarWorks, 2018. https://scholarworks.wm.edu/etd/1550153840.
Повний текст джерелаRaad, Patrick. "Protocol architecture and algorithms for distributed data center networks." Thesis, Paris 6, 2015. http://www.theses.fr/2015PA066571/document.
Повний текст джерелаWhile many business and personal applications are being pushed to the cloud, offering a reliable and a stable network connectivity to cloud-hosted services becomes an important challenge to face in future networks. In this dissertation, we design advanced network protocols, algorithms and communication strategies to cope with this evolution in distributed data center architectures. We propose a user-centric distributed cloud network architecture that is able to: (i) migrate virtual resources between data centers with an optimized service downtime; (ii) offer resilient access to virtual resources; (iii) minimize the cloud access latency. We identify two main decision making problems: the virtual machine orchestration problem, also taking care of user mobility, and the routing locator switching configuration problem, taking care of both extra and intra data center link states. We evaluate our architecture using real test beds of geographically distributed data centers, and we also simulate realistic scenarios based on real mobility traces. We show that migrating virtual machines between data centers at negligible downtime is possible by enhancing overlay protocols. We then demonstrate that by linking cloud virtual resource mobility to user mobility we can get a considerable gain in the transfer rates. We prove by simulations using real traces that the virtual machine placement decision is more important than the routing locator switching decision problem when the goal is to increase the connection throughput: the cloud access performance is primarily affected by the former decision, while the latter decision can be left to intra data center traffic engineering solutions. Finally, we propose solutions to take profit from multipath transport protocols for accelerating cloud access performance in our architecture, and to let link-state intra data center routing fabrics piloting the cloud access routing locator switching
de, Carvalho Tiago Filipe Rodrigues. "Integrated Approach to Dynamic and Distributed Cloud Data Center Management." Research Showcase @ CMU, 2016. http://repository.cmu.edu/dissertations/739.
Повний текст джерелаLi, Dawei. "On the Design and Analysis of Cloud Data Center Network Architectures." Diss., Temple University Libraries, 2016. http://cdm16002.contentdm.oclc.org/cdm/ref/collection/p245801coll10/id/413608.
Повний текст джерелаPh.D.
Cloud computing has become pervasive in the IT world, as well as in our daily lives. The underlying infrastructures for cloud computing are the cloud data centers. The Data Center Network (DCN) defines what networking devices are used and how different devices are interconnected in a cloud data center; thus, it has great impacts on the total cost, performances, and power consumption of the entire data center. Conventional DCNs use tree-based architectures, where a limited number of high-end switches and high-bandwidth links are used at the core and aggregation levels to provide required bandwidth capacity. A conventional DCN often suffers from high expenses and low fault-tolerance, because high-end switches are expensive and a failure of such a high-end switch will result in disastrous consequences in the network. To avoid the problems and drawbacks in conventional DCNs, recent works adopt an important design principle: using Commodity-Off-The-Shelf (COTS) cheap switches to scale out data centers to large sizes, instead of using high-end switches to scale up data centers. Based on this scale-out principle, a large number of novel DCN architectures have been proposed. These DCN architectures are classified into two categories: switch-centric and server-centric DCN architectures. In both switch-centric and server-centric architectures, COTS switches are used to scale out the network to a large size. In switch-centric DCNs, routing intelligence is placed on switches; each server usually uses only one port of the Network Interface Card (NIC) to connect to the switches. In server-centric DCNs, switches are only used as dummy cross-bars; servers in the network serve as both computation nodes and packet forwarding nodes that connect switches and other servers, and routing intelligence is placed on servers, where multiple NIC ports may be used. This dissertation considers two fundamental problems in designing DCN architectures using the scale-out principle. The first problem considers how to maximize the total number of dual-port servers in a server-centric DCN given a network diameter constraint. Motivated by the Moore Bound, which provides the upper bound on the number of nodes in a traditional graph given a node degree and diameter, we give an upper bound on the maximum number of dual-port servers in a DCN, given a network diameter constraint and a switch port number. Then, we propose three novel DCN architectures, SWCube, SWKautz, and SWdBruijn, whose numbers of servers are close to the upper bound, and are larger than existing DCN architectures in most cases. SWCube is based on the generalized hypercube. SWCube accommodates a comparable number of servers to that of DPillar, which is the largest existing one prior to our work. SWKautz and SWdBruijn are based on the Kautz graph and the de Bruijn graph, respectively. They always accommodate more servers than DPillar. We investigate various properties of SWCube, SWKautz, and SWdBruijn; we also compare them with various existing DCN architectures and demonstrate their advantages over existing architectures. The second problem focuses on the tradeoffs between network performances and power consumption in designing DCN architectures. We have two motivations for our work. The first one is that most existing works take extreme designs in terms of improving network performances and reducing the power consumption. Some DCNs use too many networking devices to improve the performances; their power consumption is very high. Other DCNs use two few networking devices, and their performances are very poor. We are interested in exploring the quantitative tradeoffs between network performances and power consumption in designing DCN architectures. The second motivation is that there do not exist important unified performance and power consumption metrics for general DCNs. Thus, we propose two important unified performance and power consumption metrics. Then, we propose three novel DCN architectures that achieve important tradeoff points in the design spectrum: FCell, FSquare, and FRectangle. Besides, we find that in all these three new architectures, routing intelligence can be placed on both servers and switches; thus they enjoy the advantages of both switch-centric and server-centric architectures, and can be regarded as a new category of DCN architectures, the dual-centric DCN architectures. We also investigate various other properties for our proposed architectures and verify that they are excellent candidates for practical cloud data centers.
Temple University--Theses
Macias, Lloret Mario. "Business-driven resource allocation and management for data centres in cloud computing markets." Doctoral thesis, Universitat Politècnica de Catalunya, 2014. http://hdl.handle.net/10803/144562.
Повний текст джерелаIzumo, Naoki. "Clouded space: Internet physicality." Thesis, University of Iowa, 2017. https://ir.uiowa.edu/etd/5515.
Повний текст джерелаDab, Boutheina. "Optimization of routing and wireless resource allocation in hybrid data center networks." Thesis, Paris Est, 2017. http://www.theses.fr/2017PESC1068/document.
Повний текст джерелаThe high proliferation of smart devices and online services allows billions of users to connect with network while deploying a vast range of applications. Particularly, with the advent of the future 5G technology, it is expected that a tremendous mobile and data traffic will be crossing Internet network. In this regard, Cloud service providers are urged to rethink their data center architectures in order to cope with this unprecedented traffic explosion. Unfortunately, the conventional wired infrastructures struggle to resist to such a traffic growth and become prone to serious congestion problems. Therefore, new innovative techniques are required. In this thesis, we investigate a recent promising approach that augments the wired Data Center Network (DCN) with wireless communications. Indeed, motivated by the feasibility of the new emerging 60 GHz technology, offering an impressive data rate (≈ 7 Gbps), we envision, a Hybrid (wireless/wired) DCN (HDCN) architecture. Our HDCN is based on i) Cisco’s Massively Scalable Data Center (MSDC) model and ii) IEEE 802.11ad standard. Servers in the HDCN are regrouped into racks, where each rack is equipped with a: i) Ethernet top-of-rack (ToR) switch and ii) set of wireless antennas. Our research aims to optimize the routing and the allocation of wireless resources for inter-rack communications in HDCN while enhancing network performance and minimizing congestion. The problem of routing and resource allocation in HDCN is NP-hard. To deal with this difficulty, we will tackle the problem into three stages. In the first stage, we consider only one-hop inter-rack communications in HDCN, where all communicating racks are in the same transmission range. We will propound a new wireless channel allocation approach in HDCN to hardness both wireless and wired interfaces for incoming flows while enhancing network throughput. In the second stage, we deal with the multi-hop communications in HDCN where communicating racks can not communicate in one single-hop wireless path. We propose a new approach to jointly route and allocate channels for each single communication flow, in an online way. Finally, in the third stage, we address the batched arrival of inter-rack communications to the HDCN so as to further optimize the usage of wireless and wired resources. For that end, we propose: i) a heuristic-based and ii) an approximate, solutions, to solve the joint batch routing and channel assignment. Based on extensive simulations conducted in QualNet simulator while considering the full protocol stack, the obtained results for both real workload and uniform traces, show that our proposals outperform the prominent related strategies
Sanhaji, Ali. "Nouveaux paradigmes de contrôle de congestion dans un réseau d'opérateur." Phd thesis, Toulouse, INPT, 2016. http://oatao.univ-toulouse.fr/17304/1/sanhaji.pdf.
Повний текст джерелаSonklin, Chanipa. "Minimising the energy consumption of data centres by genetic algorithms." Thesis, Queensland University of Technology, 2020. https://eprints.qut.edu.au/198050/1/Chanipa_Sonklin_Thesis.pdf.
Повний текст джерелаFrancischetti, Emilio Junior. "Garanzie del servizio in ambienti di cloud computing: uno studio sperimentale." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2011. http://amslaurea.unibo.it/2323/.
Повний текст джерелаBilal, Kashif. "Analysis and Characterization of Cloud Based Data Center Architectures for Performance, Robustness, Energy Efficiency, and Thermal Uniformity." Diss., North Dakota State University, 2014. https://hdl.handle.net/10365/27323.
Повний текст джерелаKnauth, Thomas. "Energy Efficient Cloud Computing: Techniques and Tools." Doctoral thesis, Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2015. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-164391.
Повний текст джерелаLópez, Saavedra Alejandra Esperanza. "Evaluación e implementación del rediseño del proceso de gestión de incidentes en el Data Center & Cloud de Sonda S.A." Tesis, Universidad de Chile, 2017. http://repositorio.uchile.cl/handle/2250/151226.
Повний текст джерелаHangwei, Qian. "Dynamic Resource Management of Cloud-Hosted Internet Applications." Case Western Reserve University School of Graduate Studies / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=case1338317801.
Повний текст джерелаSutrisno, Harry. "Techno-Economic Study on The Alternative Power and Cooling Systems Design for Cost & Energy-Efficient Edge Cloud Data Center(s)." Thesis, KTH, Skolan för industriell teknik och management (ITM), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-302990.
Повний текст джерела5G-tekniken har möjliggjort prestandakänsliga applikationer med låg latens och höga bandbreddskrav, vilket har ställt högre krav på låg latens för datatjänster. För att möta detta behov förutspås ett småskaligt datacenter - edge cloud – växa i framtiden. På grund av dess användarnära natur kan tillväxten av edge clouds i tätområden orsaka problem med det befintliga kraftsystemet. Förutom denna kraftsystemutmaning kräver edge cloud också en högre resurskostnad än storskaliga datacenter på grund av skalfördelarna. I denna avhandling introduceras fyra alternativa energi- och kyltekniker för att hantera dessa utmaningar. Dessa fyra tekniker är solpanel, vertikalaxel vindturbin (VAWT), bakdörrvärmeväxlare (RDHx), och nedsänkningskylning. Detaljerad information om edge cloud erfordras för att förstå bidraget från dessa fyra tekniker. På grund av edge clouds tidiga stadium är all nödvändig data dock inte tillgänglig, vaför antaganden om görs. Förutom det krävs också en kostnadsmodell för edge cloud för att visa hur betydande bidraget från den alternativa tekniken är om den jämförs med den totala ägandekostnaden. I denna avhandling utökas kostnadsmodellen för edge cloud för de alternativa energi- och kylsystemscenarierna. Med antagen data för ett edge cloud genomförs en känslighetsanalys för att avgöra om alternativa energi- och kyltekniker kan sänka kostnaden för edge cloud-resurser eller inte. Kostnadsmodelleringen visar att VAWT och nedsänkningskylning inte är möjlig för det specifika antagna datacentret. Å andra sidan kan solpanel spara 4,55% av datacentrets elförbrukning (motsvarande 0,21% minskning av den totala kostnaden när den beräknas med det aktuella elpriset). Dessutom presterade RDHx bättre med 22,73% av datacenters elutgifter (motsvarande 8,35% av besparingen från totalkostnaden när den beräknas med det aktuella elpriset).
Khaleel, Ali. "Optimisation of a Hadoop cluster based on SDN in cloud computing for big data applications." Thesis, Brunel University, 2018. http://bura.brunel.ac.uk/handle/2438/17076.
Повний текст джерелаVítek, Daniel. "Cloud computing s ohledem na technologické aspekty a změny v infrastruktuře." Master's thesis, Vysoká škola ekonomická v Praze, 2010. http://www.nusl.cz/ntk/nusl-72548.
Повний текст джерелаZhang, Yuan [Verfasser], Xiaoming [Akademischer Betreuer] Fu, K. K. [Akademischer Betreuer] Ramakrishnan, Dieter [Akademischer Betreuer] Hogrefe, Winfried [Akademischer Betreuer] Kurth, and Carsten [Akademischer Betreuer] Damm. "Dynamic Resource Scheduling in Cloud Data Center / Yuan Zhang. Betreuer: Xiaoming Fu. Gutachter: K. K. Ramakrishnan ; Dieter Hogrefe ; Winfried Kurth ; Carsten Damm." Göttingen : Niedersächsische Staats- und Universitätsbibliothek Göttingen, 2015. http://d-nb.info/1078150753/34.
Повний текст джерелаPaolucci, Fabio. "Migrazione concorrente di macchine virtuali su piattaforme open source." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2015. http://amslaurea.unibo.it/8454/.
Повний текст джерелаMohammed, Bashir. "A Framework for Efficient Management of Fault Tolerance in Cloud Data Centres and High-Performance Computing Systems: An Investigation and Performance analysis of a Cloud Based Virtual Machine Success and Failure Rate in a typical Cloud Computing Environment and Prediction Methods." Thesis, University of Bradford, 2019. http://hdl.handle.net/10454/17400.
Повний текст джерелаDegoutin, Stéphane. "Société-nuage." Thesis, Paris Est, 2019. http://www.theses.fr/2019PESC1009.
Повний текст джерелаThis book unfolds, like a Chinese landscape painting through which the viewer’s gaze wanders slowly. I describe a panorama. It is not made of mountains in the mist or bushes swept by the wind, but of data centers, automated warehouses, social network feeds...I explore the hypothesis that the Internet is part of a general process that reduces society and materials to small-scale components, which allow its mechanisms to become more fluid. A chemist’s idea – the decomposition of matter into powder to facilitate its recomposition – is also applied to social relations, memory and humans in general.Just as the reduction of matter accelerates chemical reactions, the reduction of society to powder allows for an accelerated decomposition and recomposition of all from which humans are made. It allows to multiply the reactions within society, to accelerate the productions of humanity and the social chemistry : combination of human passions (Charles Fourier), hyperfragmentation of work (Mechanical Turk), decomposition of knowledge (Paul Otlet), Internet of neurons (Michael Chorost), agregation of micro affects (Facebook). This is what I call the « society as cloud »