Academic literature on the topic 'Load sharing, Energy balancing'
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Journal articles on the topic "Load sharing, Energy balancing"
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Hossain, Md Sanwar, Khondoker Ziaul Islam, Abu Jahid, Khondokar Mizanur Rahman, Sarwar Ahmed, and Mohammed H. Alsharif. "Renewable Energy-Aware Sustainable Cellular Networks with Load Balancing and Energy-Sharing Technique." Sustainability 12, no. 22 (November 10, 2020): 9340. http://dx.doi.org/10.3390/su12229340.
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With the proliferation of cellular networks, the ubiquitous availability of new-generation multimedia devices, and their wide-ranging data applications, telecom network operators are increasingly deploying the number of cellular base stations (BSs) to deal with unprecedented service demand. The rapid and radical deployment of the cellular network significantly exerts energy consumption and carbon footprints to the atmosphere. The ultimate objective of this work is to develop a sustainable and environmentally-friendly cellular infrastructure through compelling utilization of the locally available renewable energy sources (RES) namely solar photovoltaic (PV), wind turbine (WT), and biomass generator (BG). This article addresses the key challenges of envisioning the hybrid solar PV/WT/BG powered macro BSs in Bangladesh considering the dynamic profile of the RES and traffic intensity in the tempo-spatial domain. The optimal system architecture and technical criteria of the proposed system are critically evaluated with the help of HOMER optimization software for both on-grid and off-grid conditions to downsize the electricity generation cost and waste outflows while ensuring the desired quality of experience (QoE) over 20 years duration. Besides, the green energy-sharing mechanism under the off-grid condition and the grid-tied condition has been critically analyzed for optimal use of green energy. Moreover, the heuristic algorithm of the load balancing technique among collocated BSs has been incorporated for elevating the throughput and energy efficiency (EE) as well. The spectral efficiency (SE), energy efficiency, and outage probability performance of the contemplated wireless network are substantially examined using Matlab based Monte–Carlo simulation under a wide range of network configurations. Simulation results reveal that the proper load balancing technique pledges zero outage probability with expected system performance whereas energy cooperation policy offers an attractive solution for developing green mobile communications employing better utilization of renewable energy under the proposed hybrid solar PV/WT/BG scheme.
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Gruosso, Giambattista, and Fredy Orlando Ruiz. "Electric Vehicle Fleets as Balancing Instrument in Micro-Grids." Energies 14, no. 22 (November 15, 2021): 7616. http://dx.doi.org/10.3390/en14227616.
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Micro-grids have become the building block of modern energy systems, where distributed resources are the characterizing feature. The charging operation of electric vehicles can be exploited as a flexible load to achieve operational goals of the micro-grid. In the particular case of car-sharing fleets, the degrees of freedom in the charging procedures are reduced when compared to private users. In this work, we illustrate how a car sharing fleet can be incorporated as a flexible load in the micro-grid management system. A linear optimization problem is formulated, where the cost function makes a trade-off between the gain in flexibility in the micro-grid and the loss incurred by the car-sharing service for delaying the recharging procedure of the EV. The proposed approach is evaluated on a data set of charging events generated by a real car-sharing fleet showing that the EMS allows reducing the daily peak demand requested to the public grid and diminishes the operational costs.
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Teekaraman, Yuvaraja, K. A. Ramesh Kumar, Ramya Kuppusamy, and Amruth Ramesh Thelkar. "SSNN-Based Energy Management Strategy in Grid Connected System for Load Scheduling and Load Sharing." Mathematical Problems in Engineering 2022 (January 10, 2022): 1–9. http://dx.doi.org/10.1155/2022/2447299.
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The proposed research work focused on energy management strategy (EMS) in a grid connected system working in islanding mode with the connected renewable energy resources and battery storage system. The energy management strategy developed provides a balancing operation at its output by utilizing perfect load sharing strategy. The EMS technique using smart superficial neural network (SSNN) is simulated, and numerical analyses are presented to validate the effectiveness of the centralized energy management strategy in a grid connected islanded system. A SSNN prediction model is unified to forecast the associated household load demand, PV generation system under various time horizons (including the disaster condition), EV availability, and status on EV section and distance. SSNN is one the most reliable forecasting methods in many of the applications. The developed system is also accounted for degradation battery model and its associated cost. The incorporation of energy management strategy (EMS) reduces the amount of energy drawn from the grid connected system when compared with the other optimized systems.
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John Paul Antony, T., and S. P. Victor. "Eslba Load Sharing Technique for Reputation Manager in Multiple Gateways." International Journal of Engineering & Technology 7, no. 3.34 (September 1, 2018): 24. http://dx.doi.org/10.14419/ijet.v7i3.34.18709.
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Every node has the states of its neighbors such as Selfish, Unselfish and No Information state. The selfish node free path is constructed by avoiding selfish node in the route discovery process. Watch Dog mechanism helps to avoid such issues. Price and Reputation system (P&RS) helps to diminish the selfish nodes in a successful manner. Trustable node with low portability will go about as a Notoriety Manager and it keeps every one of the records of every node in a record system. The overload of RA leads to various problem and makes the communication very slow. In this paper we discuss about the RA affiliation and request in various possible ways. RA sends the affiliation to the nearest relay node to act as a RA for few nodes. Moreover we discuss the RA communication with Internet through Gateways and the load balancing algorithm – Energy Share Load Balancing Algorithm (ESLBA). The heap adjusting algorithm shares the heap between the nodes and channelizes the ideal course smarterly.
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Wahid, Abdul, Javed Iqbal, Affaq Qamar, Salman Ahmed, Abdul Basit, Haider Ali, and Omar M. Aldossary. "A Novel Power Scheduling Mechanism for Islanded DC Microgrid Cluster." Sustainability 12, no. 17 (August 25, 2020): 6918. http://dx.doi.org/10.3390/su12176918.
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Extension of the main grid to remote areas is economically not feasible. To electrify remote areas, one of the best choices is to install Renewable Energy Sources (RES) as a distributed generation (DG) and thus form a microgrid (MG) in islanded (Stand-alone) mode. In islanded mode, the MG has no support from the national grid. Thus, the overloading of islanded DC MG can collapse DC bus voltage and cause fluctuation in the load. Therefore, the power sharing and the interconnection among the microgrid (MG) cluster are necessary for reliable operation. Many methods for power sharing also aim at minimizing circulating currents which cannot be avoided when every MG feeds their load locally. Therefore, the proper power balancing among generation, loads, and in between MG cluster is challenging in islanded topology. This paper presents an intelligent controller for power sharing among PV-based MG clusters with load management of connected load during power deficiency. The priority is given to the local critical load of each MG. The second priority is given to the remaining load of the respective MG. The least priority is given to the loads connected to the neighboring MGs. The results show that the power continuation to the power-deficient load has been maintained when another MG has surplus power. The circulating current losses between the MG cluster has been fully avoided during no power sharing.
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Raj D, Chethan, and D. N. Gaonkar. "Multiple Inverters Operated in Parallel for Proportional Load Sharing in Microgrid." International Journal of Power Electronics and Drive Systems (IJPEDS) 8, no. 2 (June 1, 2017): 654. http://dx.doi.org/10.11591/ijpeds.v8.i2.pp654-666.
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<p class="a">The new energy source utilization and development, gradual rise of distributed power grid miniaturization, intelligence, control has become a trend. In order to make microgrid reliable and efficiently run, control technology of microgrid has become a top priority and an inverter as microgrid basic unit, its control has become the most important part in microgrid. In this paper, three inverters are operated in parallel using an P-V/Q-F droop control is investigated. Mathematical model of three phase inverter with LC filter is derived, which is based on the voltage and current dual control loop. Parallel control strategy based on P-V/Q-F droop control, does not require a real time communications between the inverters and more suitable for microgrid applications. To verify the feasibility and validity of the droop control scheme, simulation is done in Matlab/Simulink and results indicate droop control has significant effect on power sharing and balancing the voltage magnitude, frequency.</p>
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Hamidi, Meryem, Abdelhadi Raihani, Mohamed Youssfi, and Omar Bouattane. "A new modular nanogrid energy management system based on multi-agent architecture." International Journal of Power Electronics and Drive Systems (IJPEDS) 13, no. 1 (March 1, 2022): 178. http://dx.doi.org/10.11591/ijpeds.v13.i1.pp178-190.
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The emergence of renewable energy sources with controllable loads gave the opportunity to the consumers to build their own Microgrids. However, the intermittence of renewable energy sources such as wind and photovoltaic leads to some challenges in terms of balancing generation and consumption. This paper aims to present a novel multi-agent model based intelligent control scheme to balance the home/building alternative current (AC)-direct current (DC) load demands and renewable energy sources. The new proposed scheme consists of a three-level hierarchical multi agent system based on cooperation, communication and interaction between intelligent agents to fulfill the load's requirements. Then, the proposed multi agent framework is simulated using four different nanogrids to prove its effectiveness using different temporal profiles for loads and generators. The proposed model is designed to be modular, so that it can be considered as a sample from a set of similar modules, assigned to different buildings to allow efficient energy sharing and balancing. The used approach in this concept is inspired from auto-similar systems, which is well suited and easy to implement on multi agent systems. A co-simulation in MATLAB and JAVA/JADE platforms has been performed regarding the production-consumption of the 24 hours baseline period.
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Elgammal, Adel, and Curtis Boodoo. "Optimal Frequency stability Control Strategy for a Grid-Connected Wind/PV/FC/BESS Coordinated with Hydroelectric Power Plant Storage Energy System Using Variable Structure Control." European Journal of Energy Research 1, no. 4 (September 13, 2021): 1–7. http://dx.doi.org/10.24018/ejenergy.2021.1.4.17.
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Because of the growing nonlinear and complexity nature of microgrid systems for example battery energy storage systems, wind-turbine fuel cell, photovoltaic, and micro hydro power plants (BESSs/FC/WT/PV/ Micro Hydro), load-frequency management has been a difficulty. The development of a load-frequency controller based on Proportional–Integral–Derivative (PID) for an autonomous microgrid (MG) with hydro, wind, and PV RES is shown in this article. The suggested LFC goal is to retain the frequency of the micro hydro power plant under variable load situations by controlling the sharing of output power constant generator between the dummy loads and consumer. Using an adaptive fuzzy logic controller to govern nearly the generating unit`s whole operation, the suggested control technique optimally chooses PID settings for each load value. The suggested fuzzy logic-based controller regulates the plant's frequency output despite fluctuating user loads and manages energy distribution by separating the micro network into separate departures connected in priority order. The suggested frequency controller uses a centralised LFC approach centred on a combination of smart load and Battery Energy Storage System to manage the MG frequency (BESS). It regulates MG frequency by providing active power balancing for a variety of events that such systems face in real-world settings, such as energy surplus generation and energy shortage. In Simulink/MATLAB, the suggested structure is simulated. The simulation results clearly demonstrate the proposed frequency controller's ability to dump extra power when the customer load varies while maintaining a consistent supply frequency.
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Demertzis, Apostolos, and Konstantinos Oikonomou. "Braided Routing Technique to Balance Traffic Load in Wireless Sensor Networks." International Journal of Monitoring and Surveillance Technologies Research 4, no. 4 (October 2016): 1–19. http://dx.doi.org/10.4018/ijmstr.2016100101.
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Many-to-one wireless sensor networks suffer from an extreme variation of traffic load between nodes. Sensor nodes near the sink consume much more energy than distant ones, resulting in the energy hole problem (global variation of load). In addition, even nodes located at the same distance from the sink experience very different traffic load with each other (local variation). This uneven distribution of traffic load, both globally and locally, results in a severe shortening of the time until first node runs out of battery. This work focuses on balancing the load of equally-distant nodes from the sink by sharing each one's load among its next-hop neighbors. Eventually, packets are travelling from node to sink by following interlaced paths. The proposed routing mechanism, called braided routing, is a simple one and can be applied over any cost-based routing, incurring a negligible overhead. Simulation results show that the local variance of load is reduced nearly 20-60% on average while the time until first death can be prolonged more than twice in many cases and the lifetime about 15%.
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Grover, Sakshi, and Mr Navtej Singh Ghumman. "POWER SAVING LOAD BALANCING STRATEGY USING DVFS IN CLOUD ENVIRONMENT." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 15, no. 13 (November 30, 2016): 7333–41. http://dx.doi.org/10.24297/ijct.v15i13.4801.
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Cloud Computing is a technology that provides a platform for the sharing of resources such as software, infrastructure, application and other information. Cloud Computing is being used widely all over the world by many IT companies as it provides benefits to the users like cost saving and ease of use. However with the growing demands of users for computing services, cloud providers are encouraged to deploy large datacenters which consume very high amount of energy resulting in carbon dioxide emissions. Power consumption is a key concern in data centers. That type of critical issues not only reduces the profit margin, but also has effect on high carbon production which is harmful for environment and living organisms. Reducing power consumption has been an important requirement for cloud resource providers not only to reduce operating costs, but also to improve system reliability. In research work, we have arranged the virtual machines in ascending order of the load. Cloudlets would be assigned to that virtual machine that has lesser load. Cloudlets are divided into three categories like high, medium and low on the basis of their instruction length. Dvfs approach which has been implemented in the paper would scale the power according to the length of the cloudlets. Three modes of Dvfs have been implemented in the research work. Various parameters like processing time, processing cost and total power consumed by all the cloudlets at the data center have been computed and analyzed. Cloudsim a toolkit for modeling and simulation of cloud computing environment has been used to implement and demonstrate the experimental results.
Dissertations / Theses on the topic "Load sharing, Energy balancing"
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Adams, Daniel Alan. "Optimal Load Balancing in a Beowulf Cluster." Link to electronic thesis, 2005. http://www.wpi.edu/Pubs/ETD/Available/etd-050205-135758/.
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Antoniadis, Antonios. "Scheduling algorithms for saving energy and balancing load." Doctoral thesis, Humboldt-Universität zu Berlin, Mathematisch-Naturwissenschaftliche Fakultät II, 2012. http://dx.doi.org/10.18452/16566.
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Diese Arbeit beschäftigt sich mit Scheduling von Tasks in Computersystemen. Wir untersuchen sowohl die in neueren Arbeiten betrachtete Zielfunktion zur Energieminimierung als auch die klassische Zielfunktion zur Lastbalancierung auf mehreren Prozessoren. Beim Speed-Scaling mit Sleep-State darf ein Prozessor, der zu jedem Zeitpunkt seine Geschwindigkeit anpassen kann, auch in einen Schlafmodus übergehen. Unser Ziel ist es, den Energieverbrauch zu minimieren. Wir zeigen die NP-Härte des Problems und klären somit den Komplexitätsstatus. Wir beweisen eine untere Schranke für die Approximationsgüte für eine spezielle natürliche Klasse von Schedules. Ferner entwickeln wir eine Familie von Algorithmen, die gute Approximationsfaktoren liefert, und zeigen, dass diese sogar Lösungen liefert, die optimal für die zuvor erwähnte Klasse von Schedules sind. Anschließend widmen wir unsere Aufmerksamkeit dem folgenden Termin-basierten Scheduling-Problem. Es seien mehrere Prozessoren gegeben, wobei jeder einzelne Prozessor zu jedem Zeitpunkt seine Geschwindigkeit anpassen kann. Ziel ist es wie zuvor, den Energieverbrauch des erzeugten Schedules zu minimieren. Für den Offline-Fall entwickeln wir einen optimalen Polynomialzeit-Algorithmus. Für das Online-Problem erweitern wir die zwei bekannten Ein-Prozessor-Algorithmen Optimal Available und Average Rate. Wir zeigen, dass diese den gleichen bzw. einen um die additive Konstante von eins vergrößerten kompetiven Faktor haben. Bei der Lastbalancierung auf mehreren Prozessoren betrachten wir Offline-Load-Balancing auf identischen Maschinen. Unser Ziel ist es, die Current-Load für temporäre Tasks mit identischem Gewicht zu minimieren. Wir zeigen, dass eine Lösung mit maximaler Imbalance von eins immer existiert und entwickeln einen effizienten Algorithmus, der solche Lösungen liefert. Zum Schluss beweisen wir die NP-Härte von zwei Verallgemeinerungen des Problems.This thesis studies problems of scheduling tasks in computing environments. We consider both the modern objective function of minimizing energy consumption, and the classical objective of balancing load across machines. We first investigate offline deadline-based scheduling in the setting of a single variable-speed processor that is equipped with a sleep state. The objective is that of minimizing the total energy consumption. Apart from settling the complexity of the problem by showing its NP-hardness, we provide a lower bound of 2 for general convex power functions, and a particular natural class of schedules. We also present an algorithmic framework for designing good approximation algorithms. Furthermore, we give tight bounds for the aforementioned particular class of schedules. We then focus on the multiprocessor setting where each processor has the ability to vary its speed. We first study the offline problem and show that optimal schedules can be computed efficiently in polynomial time. Regarding the online problem and a natural class of power functions, we extend the two well-known single-processor algorithms Optimal Available and Average Rate. We prove that Optimal Available has the same competitive ratio as in the single-processor case. For Average Rate we show a competitive factor that increases by an additive constant of one compared to the single-processor result. With respect to load balancing, we consider offline load balancing on identical machines, with the objective of minimizing the current load, for temporary unit-weight jobs. The problem can be seen as coloring n intervals with k colors, such that for each point on the line, the maximal difference between the number of intervals of any two colors is minimal. We prove that a coloring with maximal difference at most one is always possible, and develop a fast polynomial-time algorithm for generating such a coloring. Lastly, we prove that two generalizations of the problem are NP-hard.
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Padoin, Edson Luiz. "Energy-aware load balancing approaches to improve energy efficiency on HPC systems." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2016. http://hdl.handle.net/10183/140401.
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Os atuais sistemas de HPC tem realizado simulações mais complexas possíveis, produzindo benefícios para diversas áreas de pesquisa. Para atender à crescente demanda de processamento dessas simulações, novos equipamentos estão sendo projetados, visando à escala exaflops. Um grande desafio para a construção destes sistemas é a potência que eles vão demandar, onde perspectivas atuais alcançam GigaWatts. Para resolver este problema, esta tese apresenta uma abordagem para aumentar a eficiência energética usando recursos de HPC, objetivando reduzir os efeitos do desequilíbrio de carga e economizar energia. Nós desenvolvemos uma estratégia baseada no consumo de energia, chamada ENERGYLB, que considera características da plataforma, irregularidade e dinamicidade de carga das aplicações para melhorar a eficiência energética. Nossa estratégia leva em conta carga computacional atual e a frequência de clock dos cores, para decidir entre chamar uma estratégia de balanceamento de carga que reduz o desequilíbrio de carga migrando tarefas, ou usar técnicas de DVFS par ajustar as frequências de clock dos cores de acordo com suas cargas computacionais ponderadas. Como as diferentes arquiteturas de processador podem apresentam dois níveis de granularidade de DVFS, DVFS-por-chip ou DVFS-por-core, nós criamos dois diferentes algoritmos para a nossa estratégia. O primeiro, FG-ENERGYLB, permite um controle fino da frequência dos cores em sistemas que possuem algumas dezenas de cores e implementam DVFS-por-core. Por outro lado, CG-ENERGYLB é adequado para plataformas de HPC composto de vários processadores multicore que não permitem tal refinado controle, ou seja, que só executam DVFS-por-chip. Ambas as abordagens exploram desbalanceamentos residuais em aplicações interativas e combinam balanceamento de carga dinâmico com técnicas de DVFS. Assim, eles reduzem a frequência de clock dos cores com menor carga computacional os quais apresentam algum desequilíbrio residual mesmo após as tarefas serem remapeadas. Nós avaliamos a aplicabilidade das nossas abordagens utilizando o ambiente de programação paralela CHARM++ sobre benchmarks e aplicações reais. Resultados experimentais presentaram melhorias no consumo de energia e na demanda potência sobre algoritmos do estado-da-arte. A economia de energia com ENERGYLB usado sozinho foi de até 25% com nosso algoritmo FG-ENERGYLB, e de até 27% com nosso algoritmo CG-ENERGYLB. No entanto, os desequilíbrios residuais ainda estavam presentes após as serem tarefas remapeadas. Neste caso, quando as nossas abordagens foram empregadas em conjunto com outros balanceadores de carga, uma melhoria na economia de energia de até 56% é obtida com FG-ENERGYLB e de até 36% com CG-ENERGYLB. Estas economias foram obtidas através da exploração do desbalanceamento residual em aplicações interativas. Combinando balanceamento de carga dinâmico com DVFS nossa estratégia é capaz de reduzir a demanda de potência média dos sistemas paralelos, reduzir a migração de tarefas entre os recursos disponíveis, e manter o custo de balanceamento de carga baixo.Current HPC systems have made more complex simulations feasible, yielding benefits to several research areas. To meet the increasing processing demands of these simulations, new equipment is being designed, aiming at the exaflops scale. A major challenge for building these systems is the power that they will require, which current perspectives reach the GigaWatts. To address this problem, this thesis presents an approach to increase the energy efficiency using of HPC resources, aiming to reduce the effects of load imbalance to save energy. We developed an energy-aware strategy, called ENERGYLB, which considers platform characteristics, and the load irregularity and dynamicity of the applications to improve the energy efficiency. Our strategy takes into account the current computational load and clock frequency, to decide whether to call a load balancing strategy that reduces load imbalance by migrating tasks, or use Dynamic Voltage and Frequency Scaling (DVFS) technique to adjust the clock frequencies of the cores according to their weighted loads. As different processor architectures can feature two levels of DVFS granularity, per-chip DVFS or per-core DVFS, we created two different algorithms for our strategy. The first one, FG-ENERGYLB, allows a fine control of the clock frequency of cores in systems that have few tens of cores and feature per-core DVFS control. On the other hand, CGENERGYLB is suitable for HPC platforms composed of several multicore processors that do not allow such a fine-grained control, i.e., that only perform per-chip DVFS. Both approaches exploit residual imbalances on iterative applications and combine dynamic load balancing with DVFS techniques. Thus, they reduce the clock frequency of underloaded computing cores, which experience some residual imbalance even after tasks are remapped. We evaluate the applicability of our approaches using the CHARM++ parallel programming system over benchmarks and real world applications. Experimental results present improvements in energy consumption and power demand over state-of-the-art algorithms. The energy savings with ENERGYLB used alone were up to 25%with our FG-ENERGYLB algorithm, and up to 27%with our CG-ENERGYLB algorithm. Nevertheless, residual imbalances were still present after tasks were remapped. In this case, when our approaches were employed together with these load balancers, an improvement in energy savings of up to 56% is achieved with FG-ENERGYLB and up to 36% with CG-ENERGYLB. These savings were obtained by exploiting residual imbalances on iterative applications. By combining dynamic load balancing with the DVFS technique, our approach is able to reduce the average power demand of parallel systems, reduce the task migration among the available resources, and keep load balancing overheads low.
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Thiam, Cheikhou. "Anti load-balancing for energy-aware distributed scheduling of virtual machines." Toulouse 3, 2014. http://thesesups.ups-tlse.fr/2441/.
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La multiplication de l'informatique en nuage (Cloud) a abouti à la création de centres de données dans le monde entier. Le Cloud contient des milliers de nœuds de calcul. Cependant, les centres de données consomment d'énorme quantités d'énergie à travers le monde estimées à plus de 1,5 % de la consommation mondiale d'électricité et devrait continuer à croître. Une problématique habituellement étudiée dans les systèmes distribués est de répartir équitablement la charge. Mais lorsque l'objectif est de réduire la consommation électrique, ce type d'algorithmes peut mener à avoir des serveurs fortement sous chargés et donc à consommer de l'énergie inutilement. Cette thèse présente de nouvelles techniques, des algorithmes et des logiciels pour la consolidation dynamique et distribuée de machines virtuelles (VM) dans le Cloud. L'objectif principal de cette thèse est de proposer des stratégies d'ordonnancement tenant compte de l'énergie dans le Cloud pour les économies d'énergie. Pour atteindre cet objectif, nous utilisons des approches centralisées et décentralisées. Les contributions à ce niveau méthodologique sont présentées sur ces deux axes. L'objectif de notre démarche est de réduire la consommation de l'énergie totale du centre de données en contrôlant la consommation globale d'énergie des applications tout en assurant les contrats de service pour l'exécution des applications. La consommation d'énergie est réduite en désactivant et réactivant dynamiquement les nœuds physiques pour répondre à la demande des ressources. Les principales contributions sont les suivantes: - Ici on s'intéressera à la problématique contraire de l'équilibrage de charge. Il s'agit d'une technique appelée Anti Load-Balancing pour concentrer la charge sur un nombre minimal de nœuds. Le but est de pouvoir éteindre les nœuds libérés et donc de minimiser la consommation énergétique du système. - Ensuite une approche centralisée a été proposée et fonctionne en associant une valeur de crédit à chaque nœud. Le crédit d'un nœud dépend de son affinité pour ses tâches, sa charge de travail actuelle et sa façon d'effectuer ses communications. Les économies d'énergie sont atteintes par la consolidation continue des machines virtuelles en fonction de l'utilisation actuelle des ressources, les topologies de réseaux virtuels établis entre les machines virtuelles et l'état thermique de nœuds de calcul. Les résultats de l'expérience sur une extension de CloudSim (EnerSim) montrent que l'énergie consommée par les applications du Cloud et l'efficacité énergétique ont été améliorées. - Le troisième axe est consacré à l'examen d'une approche appelée "Cooperative scheduling Anti load-balancing Algorithm for cloud". Il s'agit d'une approche décentralisée permettant la coopération entre les différents sites. Pour valider cet algorithme, nous avons étendu le simulateur MaGateSim. Avec une large évaluation expérimentale d'un ensemble de données réelles, nous sommes arrivés à la conclusion que l'approche à la fois en utilisant des algorithmes centralisés et décentralisés peut réduire l'énergie consommée des centres de donnéesThe multiplication of Cloud computing has resulted in the establishment of largescale data centers around the world containing thousands of compute nodes. However, Cloud consume huge amounts of energy. Energy consumption of data centers worldwide is estimated at more than 1. 5% of the global electricity use and is expected to grow further. A problem usually studied in distributed systems is to evenly distribute the load. But when the goal is to reduce energy consumption, this type of algorithms can lead to have machines largely under-loaded and therefore consuming energy unnecessarily. This thesis presents novel techniques, algorithms, and software for distributed dynamic consolidation of Virtual Machines (VMs) in Cloud. The main objective of this thesis is to provide energy-aware scheduling strategies in cloud computing for energy saving. To achieve this goal, we use centralized and decentralized approaches. Contributions in this method are presented these two axes. The objective of our approach is to reduce data center's total energy consumed by controlling cloud applications' overall energy consumption while ensuring cloud applications' service level agreement. Energy consumption is reduced by dynamically deactivating and reactivating physical nodes to meet the current resource demand. The key contributions are: - First, we present an energy aware clouds scheduling using anti-load balancing algorithm : concentrate the load on a minimum number of severs. The goal is to turn off the machines released and therefore minimize the energy consumption of the system. - The second axis proposed an algorithm which works by associating a credit value with each node. The credit of a node depends on its affinity to its jobs, its current workload and its communication behavior. Energy savings are achieved by continuous consolidation of VMs according to current utilization of resources, virtual network topologies established between VMs, and thermal state of computing nodes. The experiment results, obtained with a simulator which extends CloudSim (EnerSim), show that the cloud application energy consumption and energy efficiency are being improved. - The third axis is dedicated to the consideration of a decentralized dynamic scheduling approach entitled Cooperative scheduling Anti-load balancing Algorithm for cloud. It is a decentralized approach that allows cooperation between different sites. To validate this algorithm, we have extended the simulator MaGateSim. With an extensive experimental evaluation with a real workload dataset, we got the conclusion that both the approach using centralized and decentralized algorithms can reduce energy consumed by data centers
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Gou, Changjiang. "Task Mapping and Load-balancing for Performance, Memory, Reliability and Energy." Thesis, Lyon, 2020. http://www.theses.fr/2020LYSEN047.
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Cette thèse se concentre sur les problèmes d'optimisation multi-objectifs survenant lors de l'exécution d'applications scientifiques sur des plates-formes de calcul haute performance et des applications de streaming sur des systèmes embarqués. Ces problèmes d'optimisation se sont tous avérés NP-complets, c'est pourquoi nos efforts portent principalement sur la conception d'heuristiques efficaces pour des cas généraux et sur la proposition de solutions optimales pour des cas particuliers.Certaines applications scientifiques sont généralement modélisées comme des arbres enracinés. En raison de la taille des données temporaires, le traitement d'une telle arborescence peut dépasser la capacité de la mémoire locale. Une solution pratique sur un système multiprocesseur consiste à partitionner l'arborescence en plusieurs sous-arbres, et à exécuter chacun d'eux sur un processeur, qui est équipé d'une mémoire locale. Nous avons étudié comment partitionner l'arbre en plusieurs sous-arbres de sorte que chaque sous-arbre tienne dans la mémoire locale et que le makespan soit minimisé, lorsque les coûts de communication entre les processeurs sont pris en compte. Ensuite, un travail pratique d'ordonnancement d'arbres apparaissant dans un solveur de matrice clairsemée parallèle est examiné. L'objectif est de minimiser le temps de factorisation en présentant une bonne localisation des données et un équilibrage de charge. La technique de cartographie proportionnelle est une approche largement utilisée pour résoudre ce problème d'allocation des ressources. Il réalise une bonne localisation des données en affectant les mêmes processeurs à de grandes parties de l'arborescence des tâches. Cependant, cela peut limiter l'équilibrage de charge dans certains cas. Basé sur une cartographie proportionnelle, un algorithme d'ordonnancement dynamique est proposé. Il assouplit le critère de localisation des données pour améliorer l'équilibrage de charge. La performance de notre approche a été validée par de nombreuses expériences avec le solveur direct à matrice clairsemée parallèle PaStiX. Les applications de streaming apparaissent souvent dans les domaines vidéo et audio. Ils se caractérisent par une série d'opérations sur le streaming de données et un débit élevé. Le système multiprocesseur sur puce (MPSoC) est un système embarqué multi / plusieurs cœurs qui intègre de nombreux cœurs spécifiques via une interconnexion haute vitesse sur une seule puce. De tels systèmes sont largement utilisés pour les applications multimédias. De nombreux MPSoC fonctionnent sur piles. Un budget énergétique aussi serré nécessite intrinsèquement un calendrier efficace pour répondre aux demandes de calcul intensives. La mise à l'échelle dynamique de la tension et de la fréquence (DVFS) peut économiser de l'énergie en diminuant la fréquence et la tension au prix d'une augmentation des taux de défaillance. Une autre technique pour réduire le coût énergétique et atteindre l'objectif de fiabilité consiste à exécuter plusieurs copies de tâches. Nous modélisons d'abord les applications sous forme de chaînes linéaires et étudions comment minimiser la consommation d'énergie sous des contraintes de débit et de fiabilité, en utilisant DVFS et la technique de duplication sur les plates-formes MPSoC.Ensuite, dans une étude suivante, avec le même objectif d'optimisation, nous modélisons les applications de streaming sous forme de graphes série-parallèle, plus complexes que de simples chaînes et plus réalistes. La plate-forme cible dispose d'un système de communication hiérarchique à deux niveaux, ce qui est courant dans les systèmes embarqués et les plates-formes informatiques hautes performances. La fiabilité est garantie par l'exécution des tâches à la vitesse maximale ou par la triplication des tâches. Plusieurs heuristiques efficaces sont proposées pour résoudre ce problème d'optimisation NP-completThis thesis focuses on multi-objective optimization problems arising when running scientific applications on high performance computing platforms and streaming applications on embedded systems. These optimization problems are all proven to be NP-complete, hence our efforts are mainly on designing efficient heuristics for general cases, and proposing optimal solutions for special cases.Some scientific applications are commonly modeled as rooted trees. Due to the size of temporary data, processing such a tree may exceed the local memory capacity. A practical solution on a multiprocessor system is to partition the tree into many subtrees, and run each on a processor, which is equipped with a local memory. We studied how to partition the tree into several subtrees such that each subtree fits in local memory and the makespan is minimized, when communication costs between processors are accounted for.Then, a practical work of tree scheduling arising in parallel sparse matrix solver is examined. The objective is to minimize the factorization time by exhibiting good data locality and load balancing. The proportional mapping technique is a widely used approach to solve this resource-allocation problem. It achieves good data locality by assigning the same processors to large parts of the task tree. However, it may limit load balancing in some cases. Based on proportional mapping, a dynamic scheduling algorithm is proposed. It relaxes the data locality criterion to improve load balancing. The performance of our approach has been validated by extensive experiments with the parallel sparse matrix direct solver PaStiX.Streaming applications often appear in video and audio domains. They are characterized by a series of operations on streaming data, and a high throughput. Multi-Processor System on Chip (MPSoC) is a multi/many-core embedded system that integrates many specific cores through a high speed interconnect on a single die. Such systems are widely used for multimedia applications. Lots of MPSoCs are batteries-operated. Such a tight energy budget intrinsically calls for an efficient schedule to meet the intensive computation demands. Dynamic Voltage and Frequency Scaling (DVFS) can save energy by decreasing the frequency and voltage at the price of increasing failure rates. Another technique to reduce the energy cost and meet the reliability target consists in running multiple copies of tasks. We first model applications as linear chains and study how to minimize the energy consumption under throughput and reliability constraints, using DVFS and duplication technique on MPSoC platforms.Then, in a following study, with the same optimization goal, we model streaming applications as series-parallel graphs, which are more complex than simple chains and more realistic. The target platform has a hierarchical communication system with two levels, which is common in embedded systems and high performance computing platforms. The reliability is guaranteed through either running tasks at the maximum speed or triplication of tasks. Several efficient heuristics are proposed to tackle this NP-complete optimization problem
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Ibrahim, Rwan. "An energy-efficient and load-balancing cluster-based routing protocol for wireless sensor networks." Thesis, McGill University, 2013. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=119428.
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Clustering is a popular routing technique in configuring Wireless Sensor Networks (WSNs). It can determine the communications between all nodes to collect data in an efficient manner. It handles the main challenge of energy-efficiency in WSNs, and can be used to re-configure the network according to changes in the nodes' conditions. This thesis contributes to the routing in WSNs by proposing an Energy-efficient and Load-balancing Cluster-based (ELC) routing algorithm for Carrier Sense Multiple Access (CSMA)-based WSNs. In particular, both distance and residual energy are taken into consideration in developing the cluster-head selection procedure while ensuring that the network has a desired number of cluster heads. In addition to distance, cluster size is also used in formulating the cost function for cluster forming in order to balance load and energy consumption among the nodes, and hence, enhancing the network lifetime. Besides, ELC employs multi-hop inter-cluster routing based on a lowest-cost path approach that considers both energy efficiency and load balancing. Illustrative simulation results show that ELC consumes less energy and offers longer network lifetime as compared to other existing cluster-based routing algorithms such as Low-Energy Adaptive Clustering Hierarchy-Centralized (LEACH-C) protocol and Central Base Station Controlled Density Aware Clustering Protocol (CBCDACP).Le clustering est une technique de routage populaire utilisée dans la configuration d'un réseau de capteurs sans fil. Cette technique peutétablir les paramètres de communication entre tous les nœuds du réseau pour une collecte de données plus efficace. Elle traite l'obstacle principal à la performance des réseaux de capteurs sans fil, l'efficacité énergétique, et peut être utilisée dans la reconfiguration du réseau selon le changement de conditions des nœuds. La contribution de cette thèse au domaine de routage dans les réseaux de capteurs sans fil consiste dans la présentation d'un nouvel algorithme de routage à base de clustering écoénergétique et d'équilibrage de charge (en anglais, Energy-efficient and Load-balancing Cluster-based routing algorithm ou ELC) pour les réseaux de capteurs sans fil à base de accès multiple avec écoute de porteuse. Particulièrement, les critères de distance et énergie résiduelle sont pris en considération dans la formulation de la procédure de sélection des Cluster Heads (CHs) tout en garantissant que le réseau est formé en tout temps par un nombre désirable de CHs. Outre que la distance, la taille du cluster est de même utilisée dans la formulation de la fonction du coût de la formation des clusters. Ceci vise à équilibrer la répartition de charges et l'énergie des nœuds du réseau, et par conséquence, à aboutir à une plus longue durée de vie du réseau. En outre, ELC emploie une technique de routage inter-cluster avec sauts multiples qui se base sur une approche au moindre coût qui prend en considération l'efficacité énergétique et l'équilibrage de charge dans le réseau. Les simulations démontrent que ELC consomme moins d'énergie et aboutit à une plus longue durée de vie du réseau par rapport à d'autres algorithmes de routage à base de clustering comme LEACH-C et CBCDACP.
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Antoniadis, Antonios [Verfasser], Susanne [Akademischer Betreuer] Albers, Christoph [Akademischer Betreuer] Dürr, and Andrzej [Akademischer Betreuer] Lingas. "Scheduling algorithms for saving energy and balancing load / Antonios Antoniadis. Gutachter: Susanne Albers ; Christoph Dürr ; Andrzej Lingas." Berlin : Humboldt Universität zu Berlin, Mathematisch-Naturwissenschaftliche Fakultät II, 2012. http://d-nb.info/1025291131/34.
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Broberg, James Andrew, and james@broberg com au. "Effective task assignment strategies for distributed systems under highly variable workloads." RMIT University. Computer Science and Information Technology, 2007. http://adt.lib.rmit.edu.au/adt/public/adt-VIT20080130.150130.
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Heavy-tailed workload distributions are commonly experienced in many areas of distributed computing. Such workloads are highly variable, where a small number of very large tasks make up a large proportion of the workload, making the load very hard to distribute effectively. Traditional task assignment policies are ineffective under these conditions as they were formulated based on the assumption of an exponentially distributed workload. Size-based task assignment policies have been proposed to handle heavy-tailed workloads, but their applications are limited by their static nature and assumption of prior knowledge of a task's service requirement. This thesis analyses existing approaches to load distribution under heavy-tailed workloads, and presents a new generalised task assignment policy that significantly improves performance for many distributed applications, by intelligently addressing the negative effects on performance that highly variable workloads cause. Many problems associated with the modelling and optimisations of systems under highly variable workloads were then addressed by a novel technique that approximated these workloads with simpler mathematical representations, without losing any of their pertinent original properties. Finally, we obtain advance queuing metrics (such as the variance of key measurements like waiting time and slowdown that are difficult to obtain analytically) through rigorous simulation.
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Chan, Kristen Y. "MULTIPLE INPUT SINGLE OUTPUT CONVERTER WITH UNEVEN LOAD SHARING CONTROL FOR IMPROVED SYSTEM EFFICIENCY." DigitalCommons@CalPoly, 2020. https://digitalcommons.calpoly.edu/theses/2139.
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This paper presents the development and study of multiple-input single-output converter (MISO) for the DC House project that utilizes a controller to maximize the overall converter’s efficiency. The premise of this thesis is to create uneven load current sharing between the converters at different loading conditions in order to maximize the efficiency of the overall MISO converter. The goal is to find a proper ratio of current from each converter to the total load current of the MISO system to achieve the greatest efficiency. The Arduino microcontroller is implemented to achieve this goal. The design and operation of the MISO converter with the proposed controller will be explained in this paper. The design and operation of the converter was tested and verified through simulation in LTSpice in addition to hardware implementation. Different ratios of current from each converter were used to fully test the MISO converter. For the 5A and 6A load current, the maximum efficiencies were reached with the 70% / 30% ratio case, with efficiencies of 94.91% and 95.07%, respectively. For 7A load current, the maximum efficiency was reached with the 60% / 40% ratio case, with an efficiency of 94.59%. The results were then compared with those obtained from the equal current sharing cases. For the cases tested, the efficiency of the unequal current sharing outperforms that obtained from the equal current sharing method.
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Patrick, Stasha Noelle. "Control of aggregate electric water heaters for load shifting and balancing intermittent renewable energy generation in a smart grid environment." Thesis, Montana State University, 2011. http://etd.lib.montana.edu/etd/2011/patrick/PatrickS1211.pdf.
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The majority of electrical energy in the United States is produced by fossil fuels, which release harmful greenhouse gas emissions and are non-renewable resources. The U.S. Department of Energy has established goals for a smart electric power grid, which facilitates the incorporation of clean, renewable generation sources, such as wind. A major challenge in incorporating renewable energy sources onto the power grid is balancing their intermittent and often unpredictable nature. In addition, wind generation is typically higher at night, when consumer demand is low. Residential electric water heaters (EWHs), which currently account for 20% of the U.S. residential daily energy demand, are the largest contributors to the morning and evening peaks in residential power demand. The simulations in this thesis tested the hypothesis that controlling the thermostat setpoints of EWHs can shift EWH electrical energy demand from hours of higher demand to hours of lower demand, provide a large percentage of the balancing reserves necessary to integrate wind energy generation onto the electric power grid, and economically benefit the customer, while maintaining safe water temperatures and without significantly increasing average daily power demand or maximum power demand of the EWHs. In the experimental simulation, during on-peak hours for demand, when electricity prices are high, the thermostat setpoints of EWHs were set to the minimum, in order to consume minimal energy. The result was that the vast majority of EWH demand occurred during off-peak hours, a significant improvement over the base case (normal operation in which no setpoint control was implemented). During off-peak hours, the thermostat setpoints of EWHs were controlled by the utility in order to provide balancing reserves necessary to maintain power system stability when wind generation is included in the system. The EWHs were able to provide the balancing reserves desired by the utility a majority of the time. In this combined control method, the customer benefitted financially by saving in electrical energy costs when compared to the base case, the EWH water temperatures always remained within safe limits. There was only a small increase in the total energy consumption, but the peak power demand did not change.
Book chapters on the topic "Load sharing, Energy balancing"
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Jia, Junbo. "Load and Energy Sharing Mechanism." In Modern Earthquake Engineering, 783–88. Berlin, Heidelberg: Springer Berlin Heidelberg, 2016. http://dx.doi.org/10.1007/978-3-642-31854-2_25.
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Cabrera, Alberto, Alejandro Acosta, Francisco Almeida, and Vicente Blanco. "Energy Efficient Dynamic Load Balancing over MultiGPU Heterogeneous Systems." In Parallel Processing and Applied Mathematics, 123–32. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-78054-2_12.
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Huang, Weihua, Zhong Ma, Xinfa Dai, Mingdi Xu, and Yi Gao. "QoS-aware adaptive load-balancing algorithm for virtual clusters." In Advances in Energy Science and Equipment Engineering II, 1839–46. Taylor & Francis Group, 6000 Broken Sound Parkway NW, Suite 300, Boca Raton, FL 33487-2742: CRC Press, 2017. http://dx.doi.org/10.1201/9781315116174-190.
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Nabi, Ausaaf, Ira Joshi, and Sonal Linda. "Effective Load Balancing and Load Sharing in Multi-access Edge Computing for Extreme Network Congestion." In Lecture Notes in Networks and Systems, 119–29. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-9228-5_11.
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Li, Xiao, and Mingchun Zheng. "An Energy-Saving Load Balancing Method in Cloud Data Centers." In Lecture Notes in Electrical Engineering, 365–73. Dordrecht: Springer Netherlands, 2013. http://dx.doi.org/10.1007/978-94-007-7618-0_35.
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Gowri, V., and B. Baranidharan. "Dynamic Energy Efficient Load Balancing Approach in Fog Computing Environment." In Intelligent Communication Technologies and Virtual Mobile Networks, 145–60. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-1844-5_13.
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Joosen, Wouter, Stijn Bijnens, Bert Robben, Johan Van Oeyen, and Pierre Verbaeten. "Flexible load balancing software for parallel applications in a time-sharing environment." In High-Performance Computing and Networking, 398–406. Berlin, Heidelberg: Springer Berlin Heidelberg, 1995. http://dx.doi.org/10.1007/bfb0046659.
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Gutiérrez-Martín, Fernando. "Pre-Investigation of Hydrogen Technologies at Large Scales for Electric Grid Load Balancing." In Transition to Renewable Energy Systems, 217–40. Weinheim, Germany: Wiley-VCH Verlag GmbH & Co. KGaA, 2013. http://dx.doi.org/10.1002/9783527673872.ch13.
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Sampayo, Sebastian L., Julien Montavont, and Thomas Noël. "eLoBaPS: Towards Energy Load Balancing with Wake-Up Radios for IoT." In Ad-Hoc, Mobile, and Wireless Networks, 388–403. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-31831-4_27.
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Padoin, Edson L., Laércio L. Pilla, Márcio Castro, Philippe O. A. Navaux, and Jean-François Méhaut. "Exploration of Load Balancing Thresholds to Save Energy on Iterative Applications." In Communications in Computer and Information Science, 76–88. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-57972-6_6.
Full textConference papers on the topic "Load sharing, Energy balancing"
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Zhang, Zhe, Donghan Shi, Chi Jin, Leong Hai Koh, Fook Hoong Choo, Peng Wang, and Yi Tang. "Droop control of a bipolar dc microgrid for load sharing and voltage balancing." In 2017 IEEE 3rd International Future Energy Electronics Conference and ECCE Asia (IFEEC 2017 - ECCE Asia). IEEE, 2017. http://dx.doi.org/10.1109/ifeec.2017.7992141.
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Sigurgeirsson, Hersir. "Parallel Computing Issues in a Particle-Continuum Model for Two-Phase Flows." In ASME 1998 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 1998. http://dx.doi.org/10.1115/imece1998-0992.
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Abstract We describe a model for two-phase flows where droplets are considered as point particles interacting with the flow, in which they are embedded, and each other. The particles interact with the flow through interchange of mass, momentum, and energy, and with each other through collisions. We investigate algorithms for computer implementation of the model using appropriate data structures to efficiently detect and handle collisions between particles, and to stably and accurately describe the particle-continuum interaction. Parallel implementation of the model poses several challenging problems, such as load balancing the particle portion of the computation and sharing data between the continuum and particle parts. We address these issues through experiments on an SGI Origin2000 and develop some simple models of computational cost.
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Botros, K. K., H. Golshan, A. Hawryluk, and B. Sloof. "Optimization of Power Train Involving Gas Turbine Driven Compressors and Aerial Coolers." In ASME 2011 Turbo Expo: Turbine Technical Conference and Exposition. ASMEDC, 2011. http://dx.doi.org/10.1115/gt2011-46841.
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Multi-objective optimizations were conducted for a compressor station comprising two dissimilar compressor units driven by two dissimilar gas turbines, two coolers of different size, and two parallel pipeline sections to the next station. Genetic algorithms were used in this optimization along with models describing the performance characteristics of gas turbines, compressors, aerial coolers, and downstream pipeline section. Essential in these models is the heat transfer between the gas and soil as it affects the pressure drop along the pipeline, and hence relates back to the coolers and compressor flow/pressure settings. Further investigative techniques were developed to also minimize NOx and CO2e emissions along with total energy consumption, i.e. fuel (used in the driver gas turbines) and electrical energy (used in the electrical fans of the aerial coolers). Two optimization scenarios were conducted: 1) Two-objective optimization of total energy consumption and NOx emission, and 2) Two-objective optimization of total energy consumption and CO2e emission. The results showed that savings in the energy consumption in the order of 5–6% is achievable with slight adjustment to unit load sharing and coolers by-pass/fan speed selections. It appears that most of the savings (around 70–75%) are derived from optimizing the load sharing between the two parallel compressors, while the balance of the savings is realized from optimizing the aerial coolers settings. In order to optimize operation for minimum NOx emission as well, a shift towards employing more of the aerial coolers is required. Preliminary cost analysis was conducted for valuation of balancing between energy consumption vs. emission loading in terms of both NOx and CO2e.
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Altman, Eitan, Urtzi Ayesta, and Balakrishna Prabhu. "Load Balancing in Processor Sharing Systems." In 3rd International ICST Conference on Performance Evaluation Methodologies and Tools. ICST, 2008. http://dx.doi.org/10.4108/icst.valuetools2008.4462.
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Nancy, J. Joys, Tamil Mani S., S. Rohith, S. Saranraj, and T. Vigneswaran. "Load Balancing using Load Sharing Technique in Distribution System." In 2020 6th International Conference on Advanced Computing and Communication Systems (ICACCS). IEEE, 2020. http://dx.doi.org/10.1109/icaccs48705.2020.9074304.
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Bhatt, Hiren H., and Hitesh A. Bheda. "Enhance load balancing using Flexible load sharing in cloud computing." In 2015 1st International Conference on Next Generation Computing Technologies (NGCT). IEEE, 2015. http://dx.doi.org/10.1109/ngct.2015.7375085.
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"RESOURCE SHARING AND LOAD BALANCING BASED ON AGENT MOBILITY." In 6th International Conference on Enterprise Information Systems. SciTePress - Science and and Technology Publications, 2004. http://dx.doi.org/10.5220/0002601303500355.
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Leino, Juha. "Approximating Optimal Load Balancing Policy in Discriminatory Processor Sharing Systems." In 2nd International ICST Conference on Performance Evaluation Methodologies and Tools. ICST, 2007. http://dx.doi.org/10.4108/smctools.2007.1929.
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Bradley, Donovan, and R. N. Uma. "Energy-efficient routing through Weighted Load Balancing." In GLOBECOM 2012 - 2012 IEEE Global Communications Conference. IEEE, 2012. http://dx.doi.org/10.1109/glocom.2012.6503086.
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Mielczarski, Wladyslaw. "Impact of Energy Storage on Load Balancing." In 2018 15th International Conference on the European Energy Market (EEM). IEEE, 2018. http://dx.doi.org/10.1109/eem.2018.8469889.
Full textReports on the topic "Load sharing, Energy balancing"
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Fowler. L51754 Field Application of Electronic Gas Admission with Cylinder Pressure Feedback for LB Engines. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), June 1996. http://dx.doi.org/10.55274/r0010363.
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�The purpose of this project was to evaluate the performance of electronic fuel gas admission valves and effects of continuous automatic cylinder balancing of large bore natural gas engines under actual field conditions. These goals have already been met under laboratory conditions at the Colorado State University Engines and Energy Conversion Laboratory in Fort Collins. The specific project objectives were to:1. Extend the feasibility of electronic fuel gas admission valves where gas valve timing and duration are varied to optimize fuel control and charge mixing from the laboratory environment to actual field applications. 2. Extend the feasibility of closed loop control using in-cylinder pressure sensors to achieve continuous, automatic power cylinder balancing from the laboratory environment to actual field applications. 3. Repeat the benefits of automatic continuous cylinder balancing shown in the laboratory testing under actual field conditions (i.e. fuel savings, improved cylinder misfire rates, improved emissions levels). In order to accomplish these objectives, the Woodward Governor Company AutoBalance TM 5000 control system was installed and tested at four host sites. Although the specific test plan differed slightly for the four host sites, the focus of the test program was consistent. The primary objective was to evaluate the effects of engine balance and the performance of the control system by testing a matrix of varying engine loads and speeds. Load and speed are the two primary control parameters affecting engine balance. Other tests were conducted to determine the effects of the electronic gas admission valve (EGAV) configuration (i.e. start of admission, end of admission, and duration).
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Cahaner, Avigdor, Sacit F. Bilgili, Orna Halevy, Roger J. Lien, and Kellye S. Joiner. effects of enhanced hypertrophy, reduced oxygen supply and heat load on breast meat yield and quality in broilers. United States Department of Agriculture, November 2014. http://dx.doi.org/10.32747/2014.7699855.bard.
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Original objectivesThe objectives of this project were to evaluate the growth performance, meat yield and quality attributes of broiler strains widely differing in their genetic potential under normal temperature vs. warm temperature (short and long-term) conditions. Strain differences in breast muscle accretion rate, metabolic responses under heat load and, gross and histopathological changes in breast muscle under thermal load was also to be characterized. BackgroundTremendous genetic progress has been made in broiler chicken growth rate and meat yield since the 1950s. Higher growth rate is driven by higher rates of feed intake and metabolism, resulting in elevated internal heat production. Hot rearing conditions negatively affect broiler growth by hindering dissipation of heat and may lead to a lethal elevation in body temperature. To avoid heat-induced mortality, broilers reduce feed intake, leading to depressed growth rate, lower weight gain, reduce breast meat yield and quality. Thus, the genetic potential of contemporary commercial broilers (CCB) is not fully expressed under hot conditions. Major conclusions, solutions, and achievementsResearch conducted in Israel focused on three broiler strains – CCB, Featherless, Feathered sibs (i.e., sharing similar genetic background). Complimentary research trials conducted at Auburn utilized CCB (Cobb 500, Cobb 700, Ross 308, Ross 708), contrasting their performance to slow growing strains. Warm rearing conditions consistently reduced feed intake, growth rate, feed efficiency, body weight uniformity and breast muscle yield, especially pronounced with CCB and magnified with age. Breast meat quality was also negatively affected, as measured by higher drip loss and paler meat color. Exposure to continuous or short-term heat stress induced respiratory alkalosis. Breast muscle histomorphometrics confirmed enhanced myofiber hypertrophy in CCB. Featherless broilers exhibited a significant increase in blood-vessel density under warm conditions. Rapid growth and muscle accretion rate was correlated to various myopathies (white striping, woody and necrotic) as well as to increases in plasma creatinekinase levels. Whether the trigger(s) of muscle damage is loss of cellular membrane integrity due to oxidative damage or tissue lactate accumulation, or to loss of inter-compartmental cation homeostasis is yet to be determined. Based on genome-wide single-nucleotide polymorphism array genotyping, identification of the gene with the recessive mutation Scaleless (sc) facilitated the development a dCAPS assay to discriminate between sc carrier (sc/+) and non-carrier (+/+) individuals. ImplicationsThis project confirmed that featherless broiler strains grow efficiently with high yield and quality of breast meat, even under warm rearing conditions that significantly depress the overall performance of CCB. Therefore, broiler meat production in hot regions and climates can be substantially improved by introducing the featherless gene into contemporary commercial broiler stocks. This approach has become more feasible with the development of dCAPS assay. A novel modification of the PCR protocol (using whole blood samples instead of extracted DNA) may contribute to the efficient development of commercial featherless broiler strains. Such strains will allow expansion of the broiler meat production in developing countries in warm climates, where energy intensive environmental control of rearing facilities are not economical and easily achievable.