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1
Renaud-Goud, Paul. "Energy-aware scheduling : complexity and algorithms". Phd thesis, Ecole normale supérieure de lyon - ENS LYON, 2012. http://tel.archives-ouvertes.fr/tel-00744247.
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In this thesis we have tackled a few scheduling problems under energy constraint, since the energy issue is becoming crucial, for both economical and environmental reasons. In the first chapter, we exhibit tight bounds on the energy metric of a classical algorithm that minimizes the makespan of independent tasks. In the second chapter, we schedule several independent but concurrent pipelined applications and address problems combining multiple criteria, which are period, latency and energy. We perform an exhaustive complexity study and describe the performance of new heuristics. In the third chapter, we study the replica placement problem in a tree network. We try to minimize the energy consumption in a dynamic frame. After a complexity study, we confirm the quality of our heuristics through a complete set of simulations. In the fourth chapter, we come back to streaming applications, but in the form of series-parallel graphs, and try to map them onto a chip multiprocessor. The design of a polynomial algorithm on a simple problem allows us to derive heuristics on the most general problem, whose NP-completeness has been proven. In the fifth chapter, we study energy bounds of different routing policies in chip multiprocessors, compared to the classical XY routing, and develop new routing heuristics. In the last chapter, we compare the performance of different algorithms of the literature that tackle the problem of mapping DAG applications to minimize the energy consumption.
2
Alabi, Derrick. "Energy-Aware Task Scheduling in Contiki". Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-348877.
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Applications for the Internet of Things often run on devices that have very limited energy capacity. Energy harvesting can offset this inherent weakness of these devices by extracting energy from the environment. Energy harvesting increases the total energy available to a device, but efficient energy consumption is still important to maximize the availability of the device. Energy-aware task scheduling is a way to efficiently consume energy in an energy constrained device with energy harvesting capabilities to extend the device's availability. In this thesis, prediction of future incoming harvest energy is combined with hard real-time and reward-based weakly-hard real-time task scheduling schemes to achieve efficient energy usage. Linear regression and artificial neural networks are evaluated individually on their ability to predict future energy harvests. The artificial neural network used contains a single hidden layer and is evaluated with ReLU, Leaky ReLU ,and sine as activation functions. The performance of linear regression and the artificial neural network with varying activation functions and number of hidden nodes are tested and compared. Linear regression is shown to be a sufficient means of predicting future energy harvests. A hard real-time and a reward-based weakly-hard real-time task scheduling scheme are also presented and compared. The experimental results show that the hard real-time scheme can extend the life of the device compared to a non-energy-aware scheduler, but the weakly-hard real-time scheme will allow the device to function indefinitely.
3
Bhatti, K. "Energy-aware Scheduling for Multiprocessor Real-time Systems". Phd thesis, Université de Nice Sophia-Antipolis, 2011. http://tel.archives-ouvertes.fr/tel-00599980.
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Les applications temps réel modernes deviennent plus exigeantes en termes de ressources et de débit amenant la conception d'architectures multiprocesseurs. Ces systèmes, des équipements embarqués au calculateur haute performance, sont, pour des raisons d'autonomie et de fiabilité, confrontés des problèmes cruciaux de consommation d'énergie. Pour ces raisons, cette thèse propose de nouvelles techniques d'optimisation de la consommation d'énergie dans l'ordonnancement de systèmes multiprocesseur. La premiére contribution est un algorithme d'ordonnancement hiérarchique á deux niveaux qui autorise la migration restreinte des tâches. Cet algorithme vise á réduire la sous-optimalité de l'algorithme global EDF. La deuxiéme contribution de cette thèse est une technique de gestion dynamique de la consommation nommée Assertive Dynamic Power Management (AsDPM). Cette technique, qui régit le contrôle d'admission des tâches, vise á exploiter de manière optimale les modes repos des processeurs dans le but de réduire le nombre de processeurs actifs. La troisiéme contribution propose une nouvelle technique, nommée Deterministic Stretch-to-Fit (DSF), permettant d'exploiter le DVFS des processeurs. Les gains énergétiques observés s'approchent des solutions déjà existantes tout en offrant une complexité plus réduite. Ces techniques ont une efficacité variable selon les applications, amenant á définir une approche plus générique de gestion de la consommation appelée Hybrid Power Management (HyPowMan). Cette approche sélectionne, en cours d'exécution, la technique qui répond le mieux aux exigences énergie/performance.
4
Alsughayyir, Aeshah Yahya. "Energy-aware scheduling in decentralised multi-cloud systems". Thesis, University of Leicester, 2018. http://hdl.handle.net/2381/42407.
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Cloud computing is an emerging Internet-based computing paradigm that aims to provide many on-demand services, requested nowadays by almost all online users. Although it greatly utilises virtualised environments for applications to be executed efficiently in low-cost hosting, it has turned energy wasting and overconsumption issues into major concerns. Many studies have projected that the energy consumption of cloud data-centres would grow significantly to reach 35% of the total energy consumed worldwide, threatening to further boost the world's energy crisis. Moreover, cloud infrastructure is built on a great amount of server equipment, including high performance computing (HPC), and the servers are naturally prone to failures. In this thesis, we study practically as well as theoretically the feasibility of optimising energy consumption in multi-cloud systems. We explore a deadline-based scheduling problem of executing HPC-applications by a heterogeneous set of clouds that are geographically distributed worldwide. We assume that these clouds participate in a federated approach. The practical part of the thesis has focused on combining two energy dimensions while scheduling HPC-applications (i.e., energy consumed for execution and data transmission). It has considered simultaneously minimising application rejections and deadline violations, to support resource reliability, with energy optimisation. In the theoretical part, we have presented the first online algorithms for the non-pre-emptive scheduling of jobs with agreeable deadlines on heterogeneous parallel processors. Through our developed simulation and experimental analysis using real parallel workloads from large-scale systems, the results evidenced that it is possible to reduce a considerable amount of energy while carefully scheduling cloud applications over a multi-cloud system. We have shown that our practical approaches provide promising energy savings with acceptable level of resource reliability. We believe that our scheduling approaches have particular importance in relation with the main aim of green cloud computing for the necessity of increasing energy efficiency.
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Bhatti, Muhammad Khurram. "Energy-aware scheduling for multiprocessor real-time systems". Nice, 2011. http://www.theses.fr/2011NICE4010.
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Les applications temps réel modernes deviennent plus exigeantes en termes de ressources et de débit amenant la conception d’architectures multiprocesseurs. Ces systèmes, des équipements embarqués au calculateur haute performance, sont, pour des raisons d’autonomie et de fiabilité, confrontés à des problèmes cruciaux de consommation d’énergie. Pour ces raisons, cette thèse propose de nouvelles techniques d’optimisation de la consommation d’énergie dans l’ordonnancement de systèmes multiprocesseur. La première contribution est un algorithme d’ordonnancement hiérarchique à deux niveaux qui autorise la migration restreinte des tâches. Cet algorithme vise à réduire la sous-optimalité de l’algorithme global EDF. La deuxième contribution de cette thèse est une technique de gestion dynamique de la consommation nommée Assertive Dynamic Power Management (AsDPM). Cette technique, qui régit le contrôle d’admission des tâches, vise à exploiter de manière optimale les modes repos des processeurs dans le but de réduire le nombre de processeurs actifs. La troisième contribution propose une nouvelle technique, nommée Deterministic Strech-to-Fit (DSF), permettant d’exploiter le DVFS des processeurs. Les gains énergétiques observés s’approchent des solutions déjà existantes tout en offrant une complexité plus réduite. Ces techniques ont une efficacité variable selon les applications, amenant à définir une approche plus générique de gestion de la consommation appelée Hybrid Power Management (HyPowMan). Cette approche sélectionne, en cours d’exécution, la technique qui répond le mieux aux exigences énergie / performanceModern real-time applications have become more sophisticated and complex in their behaviour over the time. Contemporaneously, multiprocessor architectures have emerged. Multiprocessor systems, due to their autonomy and reliability, face critical problem of energy consumption. To address this issue in real-time systems, many software-based approaches have emerged. This thesis proposes new techniques for energy-efficient scheduling of multiprocessor systems. Our first contribution is a hierarchical scheduling algorithm that allows restricted migration of tasks. This algorithm aims at reducing the sub-optimality of global EDF algorithm. The second contribution of this thesis is a dynamic power management technique called Assertive Dynamic Power Management (AsDPM). This technique is an admission control technique for real-time tasks, which decides when exactly a ready task shall execute, thereby reducing the number of active processors. The third contribution of this dissertation is a DVFS technique, referred as Deterministic Strech-to-Fit (DSF) technique, which falls in the category of inter-task DVFS techniques. Both DPM and DVFS techniques are efficient for specific operating conditions. However, they often outperform each other when these conditions change. Our fourth and final contribution is a generic power / energy management scheme, called Hybrid Power Management (HyPowMan) scheme. This scheme, instead of designing new power / energy management techniques for specific operating conditions, takes a set of well-known existing policies. At runtime, the best-performing policy for given workload is adapted by HyPowMan scheme through machine-learning approach
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Bokar, Ali. "Energy- Aware Task Scheduling Over Mobile Ad Hoc Networks". Phd thesis, METU, 2009. http://etd.lib.metu.edu.tr/upload/3/12610313/index.pdf.
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Mobile ad hoc networks (MANETs) can be formed dynamically without the support of any existing infrastructure or any centralized administration. They consist of heterogeneous mobile nodes which are powered by batteries, move arbitrarily and are connected by wireless links. Battery energy limitation is one of the main challenges in the MANETs. Several hardware and software based techniques have been proposed in this field. Most of the previous studies have considered only the energy minimization of individual nodes and disregarded the overall network lifetime. Topology management is another important problem in MANETs, in this senseseveral new computing paradigms have been developed by the researchers, and the topology management has not been studied clearly in most of these models. In this study, we propose two new techniques that deal with the topology management in order to facilitate the nodes&rsquo
cooperation towards energy saving. The developed computing model considers heterogeneous mobile nodes. A node that faces shortage in its resources (energy and processing capability) sends its work to one of the nearby devices which is able to execute the work. In addition, we propose two algorithm for dynamic and two for static task scheduling, to prolong the network life time. Comprehensive experiments showed that the proposed schemes achieve a significant improvement in the network lifetime while simultaneously reducing the energy consumption and time delay for each task.
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Nélis, Vincent. "Energy-aware real-time scheduling in embedded multiprocessor systems". Doctoral thesis, Universite Libre de Bruxelles, 2010. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/210058.
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Nowadays, computer systems are everywhere. From simple portable devices such as watches and MP3 players to large stationary installations that control nuclear power plants, computer systems are now present in all aspects of our modern and every-day life. In about only 70 years, they have completely perturbed our way of life and they reached a so high degree of sophistication that they will be soon capable of driving our cars and cleaning our houses without any human intervention. As computer systems gain in responsibilities, it becomes essential that they provide both safety and reliability. Indeed, a failure in systems such as the anti-lock braking system (ABS) in cars could threaten human lives and generate catastrophic and irreversible consequences. Hence, for many years, researchers have addressed these emerging problems of system safety and reliability which come along with this fulgurant evolution. This thesis provides a general overview of embedded real-time computer systems, i.e. a particular kind of computer system whose number grows daily. We provide the reader with some preliminary knowledge and a good understanding of the concepts that underlie this emerging technology. We focus especially on the theoretical problems related to the real-time issue and briefly summarizes the main solutions, together with their advantages and drawbacks. This brings the reader through all the conceptual layers constituting a computer system, from the software level---the logical part---that specifies both the system behavior and requirements to the hardware level---the physical part---that actually performs the expected treatments and reacts to the environment. In the meanwhile, we introduce the theoretical models that allow researchers for theoretical analyses which ensure that all the system requirements are fulfilled. Finally, we address the energy consumption problem in embedded systems. We describe the various factors of power dissipation in modern technologies and we introduce different solutions to reduce this consumption./Cette thèse se focalise sur un type de systèmes informatiques bien précis appelés “systèmes embarqués temps réel”. Un système est dit “embarqué” lorsqu’il est développé afin de servir un but bien précis. Un téléphone portable est un parfait exemple de système embarqué étant donné que toutes ses fonctionnalités sont rigoureusement définies avant même sa conception. Au contraire, un ordinateur personnel n’est généralement pas considéré comme un système embarqué, les concepteurs ne sachant pas à l’avance à quelles fins il sera utilisé. Une grande partie de ces systèmes embarqués ont des contraintes temporelles très fortes, ce qui les distingue encore plus des ordinateurs grand public. A titre d’exemple, lorsqu’un conducteur de voiture freine brusquement, l’ordinateur de bord déclenche l’application ABS et il est primordial que cette application soit traitée endéans une courte échéance. Autrement dit, cette fonctionnalité ABS doit être traitée prioritairement par rapport aux autres fonctionnalités du véhicule. Ce type de système embarqué est alors dit “temps réel”, dû à ces notions de temps et de priorités entre les applications. La problèmatique posée par les systèmes temps réel est la suivante. Comment déterminer, à tout moment, un ordre d’exécution des différentes fonctionnalités de telle sorte qu’elles soient toutes exécutées entièrement endéans leur échéance ?De plus, avec l’apparition récente des systèmes multiprocesseurs, cette problématique s’est fortement complexifiée, vu que le système doit à présent déterminer quelle fonctionnalité s’exécute à quel moment sur quel processeur afin que toutes les contraintes temporelles soient respectées. Pour finir, ces systèmes embarqués temp réel multiprocesseurs se sont rapidement retrouvés confrontés à un problème de consommation d’énergie. Leur demande en terme de performance (et donc en terme d’énergie) à évolué beaucoup plus rapidement que la capacité des batteries qui les alimentent. Ce problème est actuellement rencontré par de nombreux systèmes, tels que les téléphones portables par exemple. L’objectif de cette thèse est de parcourir les différents composants de tels système embarqués et de proposer des solutions afin de réduire leur consommation d’énergie.
Doctorat en Sciences
info:eu-repo/semantics/nonPublished
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Liu, H. "Combinatorial challenges and algorithms in new energy aware scheduling problems". Thesis, University of Liverpool, 2017. http://livrepository.liverpool.ac.uk/3008036/.
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In this thesis, we study the theoretical approach on energy-efficient scheduling problems arising in demand response management in the modern electrical smart grid. Consumers send in power requests with flexible feasible timeslots during which their requests can be served. The grid controller, upon receiving power requests, schedules each request within the specified interval. The electricity cost is measured by a convex function of the load in each timeslot. The objective is to schedule all requests with the minimum total electricity cost. We study the smart grid scheduling problem in different models. For the offline model, we prove the problem is NP-hard for the general case. We propose a polynomial time algorithm for special input where jobs have unit power request and unit time duration. By adapting the polynomial time algorithm for unit-size jobs, we propose an approximation algorithm for more general input. On the other hand, we also present an exact algorithm to find the optimal schedule for the problem with general input. For the online model, we propose an online algorithm for jobs with jobs with arbitrary power request, arbitrary time duration, and arbitrary contiguous feasible intervals. We also show a lower bound of the competitive ratio for the smart grid scheduling problem with unit height and arbitrary width. For special cases, we design different online algorithms with better competitive ratios. Finally, we look at other optimization problems and show how to solve them by adapting our techniques. We prove that our online algorithm can solve the machine minimization problem with an asymptotically optimal competitive ratio. We also show that our exact algorithm can be adapted to solve other demand response management problems.
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Han, Qiushi. "Energy-aware Fault-tolerant Scheduling for Hard Real-time Systems". FIU Digital Commons, 2015. http://digitalcommons.fiu.edu/etd/2222.
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Over the past several decades, we have experienced tremendous growth of real-time systems in both scale and complexity. This progress is made possible largely due to advancements in semiconductor technology that have enabled the continuous scaling and massive integration of transistors on a single chip. In the meantime, however, the relentless transistor scaling and integration have dramatically increased the power consumption and degraded the system reliability substantially. Traditional real-time scheduling techniques with the sole emphasis on guaranteeing timing constraints have become insufficient.
In this research, we studied the problem of how to develop advanced scheduling methods on hard real-time systems that are subject to multiple design constraints, in particular, timing, energy consumption, and reliability constraints. To this end, we first investigated the energy minimization problem with fault-tolerance requirements for dynamic-priority based hard real-time tasks on a single-core processor. Three scheduling algorithms have been developed to judiciously make tradeoffs between fault tolerance and energy reduction since both design objectives usually conflict with each other. We then shifted our research focus from single-core platforms to multi-core platforms as the latter are becoming mainstream. Specifically, we launched our research in fault-tolerant multi-core scheduling for fixed-priority tasks as fixed-priority scheduling is one of the most commonly used schemes in the industry today. For such systems, we developed several checkpointing-based partitioning strategies with the joint consideration of fault tolerance and energy minimization. At last, we exploited the implicit relations between real-time tasks in order to judiciously make partitioning decisions with the aim of improving system schedulability.
According to the simulation results, our design strategies have been shown to be very promising for emerging systems and applications where timeliness, fault-tolerance, and energy reduction need to be simultaneously addressed.
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Khaleel, Mustafa Ibrahim. "ENERGY-AWARE JOB SCHEDULING AND CONSOLIDATION APPROACHES FOR WORKFLOWS IN CLOUD". OpenSIUC, 2016. https://opensiuc.lib.siu.edu/dissertations/1165.
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Cloud computing offers several types of on-demand and scalable access to software, computing resources, and storage services through web browsers based on pay-as-you- go model. In order to meet the growing demand of active users and reduce the skyrocketing cost of electricity for powering the data centers, cloud service providers are highly motivated to implement performance guaranteed and cost-effective job schedulers. Many researchers have been focusing on scheduling jobs with high performance, and their primary concern has been execution time considerations. As a result of this thinking, little attention was paid to energy consumption and energy costs. However, nowadays energy cost has gained more and more attention from the service providers. This new reality has posed many new challenges for providers who are both concerned about meeting the execution time constraints and reducing energy costs. In recent years, there has been a growing body of research which focused on improving resource utilization by adopting new strategies and ideas that can be used to improve energy efficiency while maintaining high system throughput. One of these strategies used is known as task consolidation. This is one of the most effective techniques for increasing system-wide resource utilization. The research clearly shows that by switching o idle servers to sleep mode a vast amount of energy can be saved. In this research, a job scheduling approach called multi-procedure energy-aware heuristic scientific workflow scheduling method referred to as Time and Energy Aware Scheduling (TEAS) is proposed to tackle an energy optimization problem. This method is based on a rigorous cost and energy model that could be used to maximize resource utilization performance. The objectives focused on maximizing resource utilization and minimizing power consumption without compromising Quality of Service (QoS) such as workflow response time specified in the Service Level Agreements (SLA). The scientific applications are formulated as Directed Acycle Graph (DAG)-structured workflow to be processed as a group using virtualization techniques over cloud resources. Furthermore, the underlying cloud hardware/Virtual Machine (VM) resource availability is time-dependent because of the dual operation modes of on-demand and reservation. The resource provision and allocation algorithm can be separated into three steps with different objectives. The first step (Datacenter Selection) selects the most efficient data center to execute module applications. The second step (Time and Energy Aware Scheduling Forward Mapping) primarily focuses on estimating the execution time of scheduling a batch of workflows over VMs on underlying cloud servers and the objective is to achieve the minimum End-to-End Delay (EED). The last, and the most important step is related to the energy saving and resource utilization (Time and Energy Aware Scheduling Backward Mapping) which is concerned with minimizing energy consumption. This task is accomplished by restricting CPU usage between double thresholds and keeping the total utilization of the CPU by all the VMs allocated to a single server between these two thresholds. In addition, cloud module could migrate to other servers to either reduce the number of active servers or achieve better performance. In this case, the communication cost would be factored into the energy cost model. The performance of our algorithm is compared to algorithms such as the Pegasus Workflow Management system, Minimum Power Consumption Minimum Power Consumption (MPC-MPC) algorithm, and Greedy algorithm. The simulation results show that the Time and Energy Aware Scheduling heuristic can significantly decrease the power consumption of cloud servers with high resource utilization for the underlying clouds.
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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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Basford, Philip James. "Using an energy aware adaptive scheduling algorithm to increase sensor network lifetime". Thesis, University of Southampton, 2015. https://eprints.soton.ac.uk/375503/.
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Sensor network research is an area which has experienced rapid growth in the last decade. One area in which it is proving particularly popular is that of environmental monitoring. Areas which have benefited from environmental monitoring include; volcanoes, crops, wildlife and, the test bed used for this thesis: glaciers. One of the main challenges faced by these networks is that of power management. This becomes even more important when energy harvesting techniques are used, as the availability of energy cannot be reliably predicted. In order to address this issue, an algorithm has been developed which allows a sensor node to adapt its schedule based on the available energy. This is achieved by using the average battery voltage to approximate energy reserves, then scaling the scheduled sensing tasks accordingly. This algorithm has been designed to work with differential GPS sensors which require multiple nodes to record in synchronisation. This means that a co-ordination system has been implemented to allow synchronisation between multiple systems with no direct communication methods. This thesis makes three main contributions to sensor network research: the development of a flexible platform for gateway nodes, the development and analysis of an energy aware adaptive scheduling algorithm, and algorithms for the use of alternate communication links to provide resilience in communications. Each of these contributions has been tested in Iceland as part of a real deployment to asses how they actually perform. During this deployment it has been possible to gather more data about the Skalafellsjokull glacier than has previously been achievable.
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ALAHMADI, ABDULRAHMAN M. "ENHANCED FIRST-FIT DECREASING ALGORITHM FOR ENERGY-AWARE TASK SCHEDULING IN CLOUD". OpenSIUC, 2014. https://opensiuc.lib.siu.edu/theses/1381.
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With the emergence of many new data centers around the globe, large-scale commercial and scientific applications executed in the cloud call for efficient cloud resource management strategies to save energy without compromising the performance. According to the statistics from the Data Centre Dynamic (DCD) organization, the expected energy consumption by computer servers would increase by 19% in 2013 compared with 2012. Such a trend may continue for many years. Moreover, the estimated energy consumption of computers in the U.S. was about 2% out of the total energy consumption in 2010, which makes the IT industry the second largest pollution contributor after aviation. In this paper, a novel approach for scheduling, sharing and migrating Virtual Machines (VMs) for a bag of cloud tasks is designed and developed to reduce energy consumption within a certain execution time and high system throughput. This approach is derived from an Enhanced First Fit Decreasing (EFFD) algorithm combined with our VM reuse strategy. Furthermore, a virtual machine migration method is introduced to dynamically monitor the cloud situation for necessary migration. Our simulation results using the open source CloudReport show that EFFD with our VM reuse strategy could gain a higher resource utilization rate and lower energy consumption than regular Greedy, Round Robin (RR) and FDD without VM reuse.
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Abdullah, Saima. "Energy-efficient and network-aware message scheduling in internet of things environment". Thesis, University of Essex, 2014. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.653057.
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While majority is focusing on the sensors, communication and network aspects of IoT systems. This thesis investigates into energy efficient aspect of scheduling messages by the things/ objects in IoT. Things or objects are clustered into IoT subgroups where each subgroup has a message broker that delivers the messages originating from members to the ultimate receiver of sensed data Le.sink. This work proposes message scheduling algorithms which improves the overall efficiency of the IoT systems. It considers the network layer routing aspect to keep the energy depletion low to provide a more optimal solution by applying certain degree of cross-layer design methodology. It proves the effectiveness and efficiency both in terms of service response time and energy consumption via simulation results. Furthermore, as messages have different priorities, an algorithm is designed considering this aspects as well. Messages are classified into high priority (HP) and best effort (BE) by the corresponding Quality of Service (QoS) aware scheduling in each IoT subgroup to differentiate emergency messages from non-mission critical messages. An energy efficient backup nodes selection algorithm is presented if any node becomes non responsive due to some internal error or external reason. This approach finds an energy efficient optimal level of replacement nodes for IoT systems, while keeping in view energy of sensor devices and the cost of deployment of the backup nodes.
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ALAHMADI, ABDULRAHMAN M. "INNOVATIVE GENERIC JOB SCHEDULING FRAMEWORKS FOR CLOUD COMPUTING ENVIRONMENTS". OpenSIUC, 2019. https://opensiuc.lib.siu.edu/dissertations/1654.
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Khemapech, Ittipong. "PoRAP : an energy aware protocol for cyclic monitoring WSNs". Thesis, University of St Andrews, 2011. http://hdl.handle.net/10023/1899.
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This work starts from the proposition that it is beneficial to conserve communication energy in Wireless Sensor Networks (WSNs). For WSNs there is an added incentive for energy-efficient communication. The power supply of a sensor is often finite and small. Replenishing the power may be impractical and is likely to be costly. Wireless Sensor Networks are an important area of research. Data about the physical environment may be collected from hostile or friendly environments. Data is then transmitted to a destination without the need for communication cables. There are power and resource constraints upon WSNs, in addition WSN networks are often application specific. Different applications will often have different requirements. Further, WSNs are a shared medium system. The features of the MAC (Medium Access Control) protocol together with the application behaviour shape the communication states of the node. As each of these states have different power requirements the MAC protocol impacts upon the operation and power consumption efficiency. This work focuses on the development of an energy conservation protocol for WSNs where direct communication between sources and a base station is feasible. Whilst the multi-hop approach has been regarded as the underlying communication paradigm in WSNs, there are some scenarios where direct communication is applicable and a significant amount of communication energy can be saved. The Power & Reliability Aware Protocol has been developed. Its main objectives are to provide efficient data communication by means of energy conservation without sacrificing required reliability. This has been achieved by using direct communication, adaptive power adaptation and intelligent scheduling. The results of simulations illustrate the significance of communication energy and adaptive transmission. The relationship between Received Signal Strength Indicator (RSSI) and Packet Reception Rate (PRR) metrics is established and used to identify when power adaptation is required. The experimental results demonstrate an optimal region where lower power can be used without further reduction in the PRR. Communication delays depend upon the packet size whilst two-way propagation delay is very small. Accurate scheduling is achieved through monitoring the clock drift. A set of experiments were carried out to study benefits of direct vs. multi-hop communication. Significant transmitting current can be conserved if the direct communication is used. PoRAP is compared to Sensor-MAC (S-MAC), Berkeley-MAC (B-MAC) and Carrier Sense Multiple Access (CSMA). Parameter settings used in the Great Duck Island (GDI) a production habitat monitoring WSNs were applied. PoRAP consumes the least amount of energy.
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Cao, Fei. "Efficient Scientific Workflow Scheduling in Cloud Environment". OpenSIUC, 2014. https://opensiuc.lib.siu.edu/dissertations/802.
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Cloud computing enables the delivery of remote computing, software and storage services through web browsers following pay-as-you-go model. In addition to successful commercial applications, many research efforts including DOE Magellan Cloud project focus on discovering the opportunities and challenges arising from the computing and data-intensive scientific applications that are not well addressed by the current supercomputers, Linux clusters and Grid technologies. The elastic resource provision, noninterfering resource sharing and flexible customized configuration provided by the Cloud infrastructure has shed light on efficient execution of many scientific applications modeled as Directed Acyclic Graph (DAG) structured workflows to enforce the intricate dependency among a large number of different processing tasks. Meanwhile, the Cloud environment poses various challenges. Cloud providers and Cloud users pursue different goals. Providers aim to maximize profit by achieving higher resource utilization and users want to minimize expenses while meeting their performance requirements. Moreover, due to the expanding Cloud services and emerging newer technologies, the ever-increasing heterogeneity of the Cloud environment complicates the challenges for both parties. In this thesis, we address the workflow scheduling problem from different applications and various objectives. For batch applications, due to the increasing deployment of many data centers and computer servers around the globe escalated by the higher electricity price, the energy cost on running the computing, communication and cooling together with the amount of CO2 emissions have skyrocketed. In order to maintain sustainable Cloud computing facing with ever-increasing problem complexity and big data size in the next decades, we design and develop energy-aware scientific workflow scheduling algorithm to minimize energy consumption and CO2 emission while still satisfying certain Quality of Service (QoS) such as response time specified in Service Level Agreement (SLA). Furthermore, the underlying Cloud hardware/Virtual Machine (VM) resource availability is time-dependent because of the dual operation modes namely on-demand and reservation instances at various Cloud data centers. We also apply techniques such as Dynamic Voltage and Frequency Scaling (DVFS) and DNS scheme to further reduce energy consumption within acceptable performance bounds. Our multiple-step resource provision and allocation algorithm achieves the response time requirement in the step of forward task scheduling and minimizes the VM overhead for reduced energy consumption and higher resource utilization rate in the backward task scheduling step. We also evaluate the candidacy of multiple data centers from the energy and performance efficiency perspectives as different data centers have various energy and cost related parameters. For streaming applications, we formulate scheduling problems with two different objectives, namely one is to maximize the throughput under a budget constraint while another is to minimize execution cost under a minimum throughput constraint. Two different algorithms named as Budget constrained RATE (B-RATE) and Budget constrained SWAP (B-SWAP) are designed under the first objective; Another two algorithms, namely Throughput constrained RATE (TP-RATE) and Throughput constrained SWAP (TP-SWAP) are developed under the second objective.
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Han, Li. "Fault-tolerant and energy-aware algorithms for workflows and real-time systems". Thesis, Lyon, 2020. http://www.theses.fr/2020LYSEN013.
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Cette thèse se concentre sur deux problèmes majeurs dans le contexte du calcul haute performance:la résilience et la consommation d'énergie.Le nombre d'unités de calcul dans les superordinateurs a considérablement augmenté ces dernièresannées, entraînant une augmentation de la fréquence des pannes. Le recours à des mécanismes detolérance aux pannes est maintenant critique pour les applications utilisant un grand nombre decomposants pendant une période de temps significative. Il est par ailleurs nécessaire de minimiserla consommation énergétique pour des raisons budgétaires et environnementales. Ceci est d'autantplus important que la tolérance aux pannes nécessite une redondance en temps ou en espace quiinduit un surcoût énergétique. Par ailleurs, certaines technologies qui réduisant la consommationd'énergie ont des effets négatifs sur les performances et la résilience.Nous concevons des algorithmes d'ordonnancement pour étudier les compromis entre performance,résilience et consommation d'énergie. Dans une première partie, nous nous concentrons surl'ordonnancement des graphes de tâches sujets à des pannes. La question est alors de décider quelletâche sauvegarder afin de minimiser le temps d'exécution. Nous concevons des solutions optimalespour des classes de graphes et fournissons des heuristiques pour le cas général. Nous considéronsdans une deuxième partie l'ordonnancement de tâches périodiques indépendantes sujettes à deserreurs silencieuses dans un contexte temps-réel. Nous étudions combien de réplicats sontnécessaires et l'interaction entre dates butoir, fiabilité, et minimisation d'énergieThis thesis is focused on the two major problems in the high performance computing context: resilience and energyconsumption.To satisfy the computing power required by modern scientific research, the number of computing units insupercomputers increases dramatically in the past years. This leads to more frequent errors than expected. Obviously,failure handling is critical for highly parallel applications that use a large number of components for a significant amountof time. Otherwise, one may spend infinite time re-executing. At the other side, power management is necessary due toboth monetary and environmental constraints. Especially because resilience often calls for redundancy in time and/or inspace , which in turn consumes extra energy. In addition, technologies that reduce energy consumption often havenegative effects on performance and resilience.In this context, we re-design scheduling algorithms to investigate trade-offs between performance, resilience and energyconsumption. The first part is focused around task graph scheduling and fail-stop errors. Which task should becheckpointed (redundancy in time) in order to minimize the total execution time? The objective is to design optimalsolutions for special classes of task graphs, and to provide general-purpose heuristics for arbitrary ones. Then in thesecond part of the thesis, we consider periodically independent task sets, which is the context of real-time scheduling,and silent errors. We investigate the number of replicas (redundancy in space) that are needed, and the interplay betweendeadlines, energy minimization and reliability
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Zeng, Gang, Tetsuo Yokoyama, Hiroyuki Tomiyama y Hiroaki Takada. "A Generalized Framework for Energy Savings in Real-Time Multiprocessor Systems". IEEE, 2008. http://hdl.handle.net/2237/12101.
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Le, Trung. "Towards Sustainable Cloud Computing: Reducing Electricity Cost and Carbon Footprint for Cloud Data Centers through Geographical and Temporal Shifting of Workloads". Thèse, Université d'Ottawa / University of Ottawa, 2012. http://hdl.handle.net/10393/23082.
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Cloud Computing presents a novel way for businesses to procure their IT needs. Its elasticity and on-demand provisioning enables a shift from capital expenditures to operating expenses, giving businesses the technological agility they need to respond to an ever-changing marketplace. The rapid adoption of Cloud Computing, however, poses a unique challenge to Cloud providers—their already very large electricity bill and carbon footprint will get larger as they expand; managing both costs is therefore essential to their growth.
This thesis squarely addresses the above challenge. Recognizing the presence of Cloud data centers in multiple locations and the differences in electricity price and emission intensity among these locations and over time, we develop an optimization framework that couples workload distribution with time-varying signals on electricity price and emission intensity for financial and environmental benefits. The framework is comprised of an optimization model, an aggregate cost function, and 6 scheduling heuristics.
To evaluate cost savings, we run simulations with 5 data centers located across North America over a period of 81 days. We use historical data on electricity price, emission intensity, and workload collected from market operators and research data archives. We find that our framework can produce substantial cost savings, especially when workloads are distributed both geographically and temporally—up to 53.35% on electricity cost, or 29.13% on carbon cost, or 51.44% on electricity cost and 13.14% on carbon cost simultaneously.
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KHAN, JAWAD B. "ENERGY MANAGEMENT FOR BATTERY-POWERED RECONFIGURABLE COMPUTING PLATFORMS AND NETWORKS". University of Cincinnati / OhioLINK, 2005. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1132075678.
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Medjiah, Samir. "Optimisation des protocoles de routage dans les réseaux multi-sauts sans fil à contraintes". Thesis, Bordeaux 1, 2012. http://www.theses.fr/2012BOR14663/document.
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Durant ces dernières années, de nombreux travaux de recherches ont été menés dans le domaine des réseaux multi-sauts sans fil à contraintes (MWNs: Multihop Wireless Networks). Grâce à l'évolution de la technologie des systèmes mico-electro-méchaniques (MEMS) et, depuis peu, les nanotechnologies, les MWNs sont une solution de choix pour une variété de problèmes. Le principal avantage de ces réseaux est leur faible coût de production qui permet de développer des applications ayant un unique cycle de vie. Cependant, si le coût de fabrication des nœuds constituant ce type de réseaux est assez faible, ces nœuds sont aussi limités en capacité en termes de: rayon de transmission radio, bande passante, puissance de calcul, mémoire, énergie, etc. Ainsi, les applications qui visent l'utilisation des MWNs doivent être conçues avec une grande précaution, et plus spécialement la conception de la fonction de routage, vu que les communications radio constituent la tâche la plus consommatrice d'énergie.Le but de cette thèse est d'analyser les différents défis et contraintes qui régissent la conception d'applications utilisant les MWNs. Ces contraintes se répartissent tout le long de la pile protocolaire. On trouve au niveau application des contraintes comme: la qualité de service, la tolérance aux pannes, le modèle de livraison de données au niveau application, etc. Au niveau réseau, on peut citer les problèmes de la dynamicité de la topologie réseau, la présence de trous, la mobilité, etc. Nos contributions dans cette thèse sont centrées sur l'optimisation de la fonction de routage en considérant les besoins de l'application et les contraintes du réseau. Premièrement, nous avons proposé un protocole de routage multi-chemin "en ligne" pour les applications orientées QoS utilisant des réseaux de capteurs multimédia. Ce protocole repose sur la construction de multiples chemins durant la transmission des paquets vers leur destination, c'est-à-dire sans découverte et construction des routes préalables. En permettant des transmissions parallèles, ce protocole améliore la transmission de bout-en-bout en maximisant la bande passante du chemin agrégé et en minimisant les délais. Ainsi, il permet de répondre aux exigences des applications orientées QoS.Deuxièmement, nous avons traité le problème du routage dans les réseaux mobiles tolérants aux délais. Nous avons commencé par étudier la connectivité intermittente entre les différents et nous avons extrait un modèle pour les contacts dans le but pouvoir prédire les future contacts entre les nœuds. En se basant sur ce modèle, nous avons proposé un protocole de routage, qui met à profit la position géographique des nœuds, leurs trajectoires, et la prédiction des futurs contacts dans le but d'améliorer les décisions de routage. Le protocole proposé permet la réduction des délais de bout-en-bout tout en utilisant d'une manière efficace les ressources limitées des nœuds que ce soit en termes de mémoire (pour le stockage des messages dans les files d'attentes) ou la puissance de calcul (pour l'exécution de l'algorithme de prédiction).Finalement, nous avons proposé un mécanisme de contrôle de la topologie avec un algorithme de routage des paquets pour les applications orientés évènement et qui utilisent des réseaux de capteurs sans fil statiques. Le contrôle de la topologie est réalisé à travers l'utilisation d'un algorithme distribué pour l'ordonnancement du cycle de service (sleep/awake). Les paramètres de l'algorithme proposé peuvent être réglés et ajustés en fonction de la taille du voisinage actif désiré (le nombre moyen de voisin actifs pour chaque nœud). Le mécanisme proposé assure un compromis entre le délai pour la notification d'un événement et la consommation d'énergie globale dans le réseauGreat research efforts have been carried out in the field of challenged multihop wireless networks (MWNs). Thanks to the evolution of the Micro-Electro-Mechanical Systems (MEMS) technology and nanotechnologies, multihop wireless networks have been the solution of choice for a plethora of problems. The main advantage of these networks is their low manufacturing cost that permits one-time application lifecycle. However, if nodes are low-costly to produce, they are also less capable in terms of radio range, bandwidth, processing power, memory, energy, etc. Thus, applications need to be carefully designed and especially the routing task because radio communication is the most energy-consuming functionality and energy is the main issue for challenged multihop wireless networks.The aim of this thesis is to analyse the different challenges that govern the design of challenged multihop wireless networks such as applications challenges in terms of quality of service (QoS), fault-tolerance, data delivery model, etc., but also networking challenges in terms of dynamic network topology, topology voids, etc. Our contributions in this thesis focus on the optimization of routing under different application requirements and network constraints. First, we propose an online multipath routing protocol for QoS-based applications using wireless multimedia sensor networks. The proposed protocol relies on the construction of multiple paths while transmitting data packets to their destination, i.e. without prior topology discovery and path establishment. This protocol achieves parallel transmissions and enhances the end-to-end transmission by maximizing path bandwidth and minimizing the delays, and thus meets the requirements of QoS-based applications. Second, we tackle the problem of routing in mobile delay-tolerant networks by studying the intermittent connectivity of nodes and deriving a contact model in order to forecast future nodes' contacts. Based upon this contact model, we propose a routing protocol that makes use of nodes' locations, nodes' trajectories, and inter-node contact prediction in order to perform forwarding decisions. The proposed routing protocol achieves low end-to-end delays while using efficiently constrained nodes' resources in terms of memory (packet queue occupancy) and processing power (forecasting algorithm). Finally, we present a topology control mechanism along a packet forwarding algorithm for event-driven applications using stationary wireless sensor networks. Topology control is achieved by using a distributed duty-cycle scheduling algorithm. Algorithm parameters can be tuned according to the desired node's awake neighbourhood size. The proposed topology control mechanism ensures trade-off between event-reporting delay and energy consumption
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Schulz, Sven. "Energy aware hybrid flow shop scheduling". 2020. https://tud.qucosa.de/id/qucosa%3A73319.
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Only if humanity acts quickly and resolutely can we limit global warming' conclude more than 25,000 academics with the statement of SCIENTISTS FOR FUTURE. The concern about global warming and the extinction of species has steadily increased in recent years.
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Lai, Ting-Hsuan y 賴廷亘. "Energy-Aware Online Scheduling for Disks Storage System". Thesis, 2013. http://ndltd.ncl.edu.tw/handle/02387062210395806991.
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碩士國立清華大學
資訊工程學系
101
Driven by the growth demand for computational power by science, business and web-application has led to the creation of large-scale data centers which consume enormous amount of power. In this thesis, our goal is to minimize the energy consumption of disk storage systems that used in those datacenters. Specifically, we investigate the approach of using energy-aware disk scheduling algorithm which has been shown as a promising technique to reduce energy without causing significant system overhead and interference. In this work, we focus on the online scheduling solution. Our main contribution is to propose several heuristic online scheduling algorithms and address the following four four important challenges in our approach: (1)request prediction; (2)load variation; (3)limited scheduling resource and (4)write request. We extensively evaluate our solutions using diskSim simulator and workload traces from both real storage systems and synthetic workload generators. The results show our solution can effectively reduce energy using online scheduling techniques and overcome the four challenges in practice.
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Liu, Ta-Wei y 劉大維. "Energy aware task partition and scheduling in FPGA". Thesis, 2015. http://ndltd.ncl.edu.tw/handle/39414110631609005954.
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碩士國立臺灣科技大學
電機工程系
103
Dynamic partial reconfigurable systems with a processor and a field-programmable gate array are promising innovations for meet the requirement of mobile embedded devices demonstrating low power consumption and high performance. However, with limited battery life and chip size, the energy consumption and area allocation are critical concerns for such systems. In this study, a energy-aware hardware/software partition is presented to minimize the system energy consumption, and contention-aware task allocation is presented to minimize the area requirement and response time. The energy efficiency and schedulability of the proposed methodology was evaluated using a series of workloads, and impressive results were obtained.
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Lin, Yi-Zhan y 林毅展. "Energy-Aware Scheduling for Multiprocessor Real-Time Systems". Thesis, 2010. http://ndltd.ncl.edu.tw/handle/55358420768589232511.
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碩士國立臺灣科技大學
資訊工程系
98
Dynamic Voltage Scaling (DVS) is a technique which can effectively reduce energy consumption of a processor. On the other hand, as the progress in process, occurrence of leakage current becomes severer which leads to static power consumption. Taking both dynamic and static power consumption into consdieration, this thesis proposed an energy-aware scheduling for multiprocessor real-time systems. In real-time systems, jobs in each task must meet their deadlines. Since lower execution voltage requires longer execution time, DVS might not be applicable when the systeme is in a heavy load. While execution time is prolonged by DVS, static power consumption increased as well. How to balance between dynamic and static power consumptions is the major issue of the thesis. The proposed energy-aware scheduling algorithm contains two parts: The first part distributes tasks in the system to processors so that slack times could be better utilized. After each task is assigned to a processor, the second part of the algorithm takes care of dynamic/static energy-aware scheduling on each processor. We adopt the largest provincial energy to approach the closest scaling ratio. By adaptively changing priority of jobs, the number of context switches can be reduced. With the proposed delay scheme, the system has more chance to stay in sleep mode, which could better reduce the static power consumption. The simulation results show that the system with our energy-aware scheduling could save energy consumption up to 35%.
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Cheng, Yi-Ching y 鄭一慶. "Energy Aware Topology Construction and Scheduling for ZigBee Wireless Networks". Thesis, 2013. http://ndltd.ncl.edu.tw/handle/89498461652819994172.
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碩士淡江大學
資訊工程學系碩士在職專班
101
ZigBee is a new wireless standard that adheres to the regulations defined in IEEE802.15.4 during the development of short-distance transmission technology. The product appeal uses short-distance transmission, energy saving, small size, low costs, easy development, capability to support large number of transmission points, and low rate data transfer characteristics to satisfy broad user requirements. Currently, ZigBee is used in products in the fields of consumer electronics, short-distance commu-nication services, energy efficiency and management, medical care, home utility monitoring, high rise management automation, automated industrial production, indoor positioning, animal tracking, elec-tro-mechanical control, and lighting system management. Energy saving mechanisms have been popular research topics in recent years because of the need to achieve long-term use of ZigBee equipment. In a ZigBee network, the use of default network link mode has causes certain nodes to bear most of the data transfer load after the formation of the network. This phenomenon caused these nodes to rapidly consume electrical power. This paper uses electricity-awareness concepts to establish a network topology with electricity-awareness, achieve selection and allocation between child nodes, and extend the life of the entire network.
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Liu, Hsiang-Hsuan y 劉向瑄. "Combinatorial Challenges and Algorithms in New Energy Aware Scheduling Problems". Thesis, 2017. http://ndltd.ncl.edu.tw/handle/59kvw8.
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博士國立清華大學
資訊工程學系所
105
In this thesis, we study the theoretical approach on energy-efficient scheduling problems arising in demand response management in the modern electrical smart grid. Consumers send in power requests with flexible feasible timeslots during which their requests can be served. The grid controller, upon receiving power requests, schedules each request within the specified interval. The electricity cost is measured by a convex function of the load in each timeslot. The objective is to schedule all requests with the minimum total electricity cost. We study the smart grid scheduling problem in different models. For the offline model, we prove the problem is NP-hard for the general case. We propose a polynomial time algorithm for special input where jobs have unit power request and unit time duration. By adapting the polynomial time algorithm for unit-size jobs, we propose an approximation algorithm for more general input. On the other hand, we also present an exact algorithm to find the optimal schedule for the problem with general input. For the online model, we propose an online algorithm for jobs with jobs with arbitrary power request, arbitrary time duration, and arbitrary contiguous feasible intervals. We also show a lower bound of the competitive ratio for the smart grid scheduling problem with unit height and arbitrary width. For special cases, we design different online algorithms with better competitive ratios. Finally, we look at other optimization problems and show how to solve them by adapting our techniques. We prove that our online algorithm can solve the machine minimization problem with an asymptotically optimal competitive ratio. We also show that our exact algorithm can be adapted to solve other demand response management problems.
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Chou, Chi-lin y 周季霖. "Energy-Aware Scheduling for Embedded Real-Time Systems Rechargeable Batteries". Thesis, 2010. http://ndltd.ncl.edu.tw/handle/95004708624241432552.
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碩士國立高雄大學
資訊工程學系碩士班
98
Due to the power limited nature of embedded systems, power efficiency is one issue in the design of embedded systems. We propose a design in which an embedded system is powered by dual rechargeable batteries and the batteries don't operate simultaneously. We propose a linear programming based approach to extend the lifetime of batteries. With the proposed approach, the lifetime of a battery will be extended and the design complexity of the system will be reduced. A simulation model is built to investigate the performance of the proposed approach. The capability of the proposed approach is evaluated by a series of simulations, for which we have encouraging results.
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Jeng-WeiLee y 李振維. "Energy-Aware Routing and QoS-Guaranteed Scheduling in Mobile Wireless Networks". Thesis, 2011. http://ndltd.ncl.edu.tw/handle/98042560484483181875.
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Hung, Ssu-Wen y 洪泗紋. "Energy-Aware Task Scheduling for NoC-based Dynamic Voltage Scalable System". Thesis, 2009. http://ndltd.ncl.edu.tw/handle/37132499935295413309.
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碩士國立臺灣大學
電子工程學研究所
97
Energy-aware task assignment and scheduling over a many-core network-on-chip (MC-NoC) platform is investigated. For real time applications, time slacks of a preliminary task schedule may be exploited to conserve energy. This can be accomplished by leveraging the dynamic voltage scaling (DVS) technique to slow down clock frequency of certain cores so long as the deadline is met. In this Thesis, the task of fine-tuning an existing task assignment and schedule and using DVS to lower overall energy consumption is formulated as a graph-theoretic maximum weight clique (MWC) problem. An efficient heuristic algorithm is proposed to systematically solve this problem. A unique feature of our approach is concurrently applying DVS to slow down execution of multiple tasks to achieve better energy saving. Extensive simulations are performed to compare this proposed algorithm against leading energy-aware task scheduling algorithm and DVS algorithm. Our algorithm exhibits a 22% more energy saving than the EAS algorithm. As for energy saving in DVS process, our MWC-based method provides a 97% saving improvement over the PV-DVS algorithm.
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Ma, Yu-Ching y 馬毓晴. "Energy Aware Flow Scheduling for Data Center Network Using Genetic Algorithms". Thesis, 2013. http://ndltd.ncl.edu.tw/handle/14307447600953978958.
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碩士國立交通大學
電信工程研究所
101
Cloud computing is one of the growing technology in recent years. Data center as the core of the supporting of the entire cloud services, the topic of how to build a data center is very important. Data center should support a large number of computing and the storage and transmission of data, which needs unblocked network. However, it’s not a simple question to choose a path of the Internet which can achieve targets such as high throughput and low delay. At the same time, data centers consume huge amounts of energy to ensure performance, which causes high operational costs, and huge carbon footprints are unfriendly to the environment. Therefore, we have to consider how to reduce energy consumption and keep high performance. This thesis focus on network equipments in the data center which have rapidly growth of energy consumption recent years. The switches contribute the largest propotion of energy consumption of network equipments, so turn off unneeded switches reduce energy consumption effectively. We can develop good routing algorithm to improve energy consumption of network equipments. It’s a complicated problem to decide routing path in a short period, so we choose genetic Genetic Algorithm to achieve our goals. Genetic algorithm is one of a heuristic algorithm. It solves the optimization problem quickly by imitating the way of the natural selection. We use fat-tree topology in our simulation, and make some improvements of GA in order to fit our problem and raise the correctness of its solution.
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jerrylu y 盧慶達. "Disk Power-aware Scheduling Scheme Based-on Energy Efficient Prefetching and Caching". Thesis, 2005. http://ndltd.ncl.edu.tw/handle/23933770958561165159.
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碩士國立中興大學
資訊科學研究所
94
During the past few years, with the dramatic improvement of information technology , modern disk can transmit data in high rotational speed and provide large capacity. However, the disk energy consuming still not improved that limits mobile computer’s battery lifetime. In this paper, we build a disk power-aware scheduling scheme based on energy efficient pre-fetching and caching to extend disk idle time in the low power mode. We provide three scheduling algorithms listing as follows: 1. Disk in spinning mode task scheduling algorithm. 2. Disk in spin down mode task scheduling algorithm. 3. Task remains pre-fetch data smaller than threshold task scheduling algorithm. By applying these three power management schemes can extend mobile computer’s battery lifetime with dramatically improvement.
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Huang, Jyun-Kai y 黃峻楷. "Energy-aware Real-Time Scheduling in Three-dimensional Dynamically Partially Reconfigurable Systems". Thesis, 2012. http://ndltd.ncl.edu.tw/handle/90543272926177617308.
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碩士國立臺灣科技大學
電機工程系
101
Energy-efficient real-time task scheduling is complicated in three-dimensional dynamically partially reconfigurable systems. The problem difficulty comes from the complexity in hardware/software partition, task scheduling with precedence constraint, and task placement. In this paper, a simulated annealing approach is proposed to minimize the system energy consumption without violating timing constraints. To reduce the search time, the hardware/software priority assignment, deadline assignment, and Best-Fit placement are presented to find the better fist solution. The proposed methodology is evaluated by a series of experiments, showing positive results.
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Liu, Zi Wei y 劉子維. "Run-Time Mixed-Task Scheduling Algorithm for Energy Aware Multi-Core Systems". Thesis, 2012. http://ndltd.ncl.edu.tw/handle/71253715650034352882.
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碩士長庚大學
資訊工程學系
101
Modern IC design techniques and wireless network techniques drive explosive developments in the embedded computing, personal computing, and pervasive computing etc. Many “smart” products, e.g., smart phones, game boxes, vehicle information systems, are also proposed in an amazing time-to-market speed. To satisfy the quality of services for these products, chip makers have adopted the multi-core architecture in their microprocessor designs. The trade-off between the processor performance and the energy consumption, therefore, become the most important issues in chip design. Many conventional researches have proposed the task scheduling algorithms with the Dynamic Voltage Scaling (DVS) mechanism to solve the energy consumption problem. Most of their approaches, however, focus on scheduling periodic tasks. In most real time systems, in fact, periodic tasks and aperiodic tasks will exist simultaneously. Only a few studies have addressed this kind of mixed task set, but most of their discussions were limited in the single-core processor. In this paper, we will focus on designing an energy-saving task scheduling algorithm schedule the mixed task sets in multi-core systems. Our goal is to minimize the chip energy consumption to execute tasks but still satisfy their performance requirements. To achieve this goal, we propose a heuristic algorithm by taking full advantage of the cores’ idle time. We can apply the DVS mechanism and extend the execution time of tasks within a larger time space.
36
Pong, Chin Ching y 彭金清. "Energy and Transition-aware Task Scheduling for Dual-core Real-time Systems". Thesis, 2011. http://ndltd.ncl.edu.tw/handle/81784736441957988925.
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碩士長庚大學
資訊工程學系
99
Many embedded or portable devices have been widely used in our daily life. Currently these devices not only have energy consumption restrictions but also have large performance demands on real-time applications. To resolve such contradiction, many studies have focused their attentions on proposing the energy-aware task scheduling for dual-core or multi-core hardware platforms. These algorithms apply the dynamic voltage scaling technique to arrange task execution on cores by different supply voltages. Most of them, however, have not considered the effects of voltage transition overheads, which may defeat the benefits from original task scheduling. In this paper, instead, we propose an energy-aware task scheduling algorithm which will consider transition overheads for dual-core real-time systems. We model this problem as an integer linear programming problem, and design a heuristic algorithm to find the solutions. Experimental results show that in a dual-core processor the proposed algorithm can reduce about 25% total energy consumption with only 16% transition overheads suffered.
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Chen, Chin-Ting y 陳致廷. "An Emission-Aware Day-Ahead power scheduling system for Internet of Energy". Thesis, 2019. http://ndltd.ncl.edu.tw/handle/7wc8jt.
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碩士國立東華大學
資訊工程學系
107
The rapid development of emerging technologies and significant cost reductions offered by the utilization of solar energy and wind power have made it feasible to replace traditional power generation methods with renewable energy sources in the future. However, one thing that distinguishes renewables from currently deployed centralized power sources is that the former are categorized as intermittent energy sources. What's more, the scale of renewables is relatively small and their deployment could be described as scattered. In the recent literature, the architecture of the Internet of Energy has been proposed to replace the current smart grid in the future. However, the large volume of energy produced, the copious amounts of accompanying consumption data, and the uncertainty of the arrival times of electric vehicles and the intermittence nature of the renewable energy will result in the short-term energy management of the IoE in the future being much complicated. In this work, a hierarchical day-ahead power scheduling system based on the architecture of the IoE is proposed to tackle these complex energy management problems. Excess electricity generated in a microgrid is allocated to other microgrids facing power supply shortages, whereby the maximal usage of distributed renewables and a reduction of the burden on traditional power generation during time periods of peak load can be achieved. Flexible charging mechanism of moving electric vehicles is also considered in the proposed scheduling system to provide preferred charging options for moving EVs and flatten the load profile simultaneously. The experimental results show that the hierarchical day-ahead power scheduling system proposed in this work not only achieves emission reduction and balances peak and off-peak period loads in an electricity market, but also shortens the time overhead required for charging of moving EVs effectively.
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Lin, Ming Ham y 林明翰. "Energy Efficient Workload-Aware DVS Scheduling for Multi-core Real-time Embedded Systems". Thesis, 2008. http://ndltd.ncl.edu.tw/handle/79906963934612974983.
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碩士國立交通大學
網路工程研究所
96
Memory is an important shared resource in a multi-core real-time embedded system. The memory contentions between cores will lengthen the total execution time due to waiting for memory requests being served. In this thesis, we focus on the tasks partition scheduling problem while considering memory contentions in multi-core real-time embedded systems. We propose an energy efficient scheduling mechanism with consideration to the memory workload of tasks, called WAS-DVS (workload-aware scheduling-dynamic voltage scaling), which is an improvement of an existing method, LTF-MES (Largest-Task-First-Minimize-Energy-Scheduling). The main difference between ours and LTF-MES is that we consider the execution order of tasks that may reduce the frequency of memory contentions. Simulation results show that by reducing memory contentions between tasks, the slack time will increase and the proposed WAS-DVS can use it to lower total execution time and total energy consumption on a variety of workloads in multi-core systems. The proposed WAS-DVS can lower the total execution time from 2% to 10.3% before applying DVS and improve the total energy consumption from 3.85% to 19% compared to LTF-MES, under various numbers of tasks and 2 to 16 cores after applying DVS.
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Liu, Yen-Fang y 劉晏芳. "Energy-aware Soft Real-time Global Scheduling with Synchronization in Multi-core System". Thesis, 2017. http://ndltd.ncl.edu.tw/handle/78488628539510150315.
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碩士國立臺灣科技大學
電機工程系
105
With increased battery-supplied mobile embedded systems, energy-aware real-time scheduling has been getting attention. However, most of the prior work is focused on the partition-based scheduler. In this paper, an energy-aware global-based synchronization is proposed to consider the task model with resource sharing in symmetric multicore embedded systems. To better trade-off between run-time response management and energy conservation, instead of meeting the hard real-time consideration, the dynamic frequency scaling with tardiness bound guarantee is presented.
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Chen, Tsai-Hsiung y 陳再興. "Energy-Aware Scheduling of Weakly-Hard Real-Time System with I/O Device". Thesis, 2012. http://ndltd.ncl.edu.tw/handle/83990948204218856509.
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碩士國立高雄大學
資訊工程學系碩士班
100
In addition to processors, embedded systems also have some peripheral devices (such as: memory, flash memory, wireless interface). These devices will also consume energy. Dynamic power management (DPM) technology is often used to minimize the energy consumption of peripheral devices with the timeout mechanism in which the device is switched to the idle state for a specific time interval. Because the requirement of some systems is to support deterministic QoS for real-time systems, rather than 100% guarantees or the probabilistic QoS, the system must support the statistical and the lowest limit of QoS, such as (m, k) constraints, which require that at least m out of any k consecutive jobs of a task meet their deadlines. We proposed search-tree-based energy-efficient algorithm to solve the scheduling problem of weakly-hard real-time system with an I/O device. An analytic study on the proposed algorithms is presented, and a series of simulation experiments are conducted to verify the analytic results and to show the capability of the proposed algorithm.
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Li, Ju-Mei y 李如梅. "Energy-Aware Node Placement, Topology Control and MAC Scheduling for Mesh-based Wireless Sensor Networks". Thesis, 2005. http://ndltd.ncl.edu.tw/handle/29754307390048755307.
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碩士淡江大學
資訊工程學系碩士班
93
Wireless sensor networks (WSNs) comprise a sink node and a large number of sensor nodes. In the application of environmental monitoring, sensor nodes that are deployed far away from the sink node transmit the gathered information to the sink node in a multi-hop manner. Therefore, sensor nodes nearby the sink node tend to exhaust their energy earlier than other nodes due to their heavy traffic for packet forwarding. The unbalanced power consumption among sensor nodes may cause network partitioned. This paper proposes efficient node placement, topology control, and MAC scheduling protocols to prolong the sensor network lifetime, reduce the packet transmission delay, and avoid collision. Firstly, a virtual tree topology is constructed based on mesh-based WSNs. Then two node-placement techniques, namely distance-based and density-based deployments are proposed to balance the power consumption of sensor nodes. Finally, a collision-free MAC scheduling protocol is proposed to prevent the packet transmissions from collision. In addition, extension of the proposed protocols are made from the mesh-based WSN to the random deployed WSN, making the mechanisms developed for Mesh-based WSNs can be applied to random deployed WSNs. Simulation results reveal that the developed protocols can efficiently balance each sensor node’s power consumption and prolong the network lifetime in both mesh-based and random deployed WSNs.
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Wang, Tzu-Chia y 王子嘉. "Layered Video Multicast with QoS-Guaranteed and Energy-Aware Scheduling Mechanisms in IEEE 802.16 Networks". Thesis, 2015. http://ndltd.ncl.edu.tw/handle/94rcah.
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博士淡江大學
資訊工程學系博士班
103
IEEE 802.16 networks characterized by long-haul and high-speed communications have attracted researchers to develop multicast schemes for wireless video services, such as mobile IPTV. Multicasting can save the bandwidth consumption and thus gains the multicast advantages. However, all MSs should cooperate with each other to wake up simultaneously for receiving the multicast data. This might reduce the power saving quality of each MS and violate the delay constraint of some MSs because all MSs in a multicast group should apply a common modulation. Therefore, we proposes the efficient QoS-guaranteed and energy-aware multicasting mechanism to maximize the multicast advantages and guarantee the delay constraint of each MS while the power-saving requirements of MSs are meet. Simulation results reveal that the proposed multicast mechanism outperforms existing works in terms of the user satisfactory and network throughput.
43
Merkel, Andreas [Verfasser]. "Task activity vectors : a novel metric for temperature-aware and energy-efficient scheduling / von Andreas Merkel". 2010. http://d-nb.info/1000439410/34.
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Wang, Bo-Hsuan y 王柏軒. "Synchronization-Aware Dynamic Thread Scheduling for Improving Performance and Saving Energy in Multi-Core Embedded Systems". Thesis, 2011. http://ndltd.ncl.edu.tw/handle/37827013294031310996.
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碩士國立中正大學
資訊工程研究所
100
Nowadays, Chip Multi-Processors (CMP) are being widely used in embedded sys- tems because they provide superior performance via parallel computing. However, they also incur a significantly large power consumption. To solve this issue, de- signers of embedded operating system must provide an efficient thread scheduling algorithm, which not only maximizes the system performance, but also minimizes the energy consumption. Further, if the scheduler makes decisions without considering the precedence relationships among threads, the decisions could conflict with the thread behavior which could result in poor performance and large energy consumption. In this Thesis, we propose a Synchronization-Aware Dynamic Thread Scheduling Algorithm (SA), which reduces the busy-waiting time caused by spinlock, and with performance improvement and energy saving. SA has two major objectives, including (1) overall high performance, in terms of less completion time, less turnaround time, less busy-waiting time, and (2) low energy consumption for all threads. The experimental results show that SA indeed improves at most performance and reduces energy consumption compared to the original scheduling algorithm in the Linux kernel version 2.6. The speedup of SA is at most 2.63 for 50 threads running on two to wight cores, and it can also saves the energy consumption by at most 50.98%. In the real-world case, that is, the Digital Video Recording (DVR) system, SA achieves at most 1.21 speedup and saves the energy consumption by at most 28.6%.
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Kommaraju, Ananda Varadhan. "Designing Energy-Aware Optimization Techniques through Program Behaviour Analysis". Thesis, 2014. http://hdl.handle.net/2005/3133.
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Green computing techniques aim to reduce the power foot print of modern embedded devices with particular emphasis on processors, the power hot-spots of these devices. In this thesis we propose compiler-driven and profile-driven optimizations that reduce power consumption in a modern embedded processor. We show that these optimizations reduce power consumption in functional units and memory subsystems with very low performance loss. We present three new techniques to reduce power consumption in processors, namely, transition aware scheduling, leakage reduction in data caches using criticality analysis, and dynamic power reduction in data caches using locality analysis of data regions.
A novel instruction scheduling technique to address leakage power consumption in functional units is proposed. This scheduling technique, transition aware scheduling, is motivated by idle periods that arise in the utilization of functional units during program execution. A continuously large idle period in a functional unit can be exploited to place the unit in low power state. This novel scheduling algorithm increases the duration of idle periods without hampering performance and drives power gating in these periods. A power model defined with idle cycles as a parameter shows that this technique saves up to 25% of leakage power with very low performance impact.
In modern embedded programs, data regions can be classified as critical and non-critical. Critical data regions significantly impact the performance. A new technique to identify such data regions through profiling is proposed. This technique along with a new criticality based cache policy is used to control the power state of the data cache. This scheme allocates non-critical data regions to low-power cache regions, thereby reducing leakage power consumption by up to 40% without compromising on the performance.
This profiling technique is extended to identify data regions that have low locality. Some data regions have high data reuse. A locality based cache policy based on cache parameters like size and associativity is proposed. This scheme reduces dynamic as well as static power consumption in the cache subsystem. This optimization reduces 25% of the total power consumption in the data caches without hampering the execution time.
In this thesis, the problem of power consumption of a program is decoupled from the number of processor cores. The underlying architecture model is simplified to abstract away a variety of processor scenarios. This simplified model can be scaled up to be implemented in various multi-core architecture models like Chip Multi-Processors, Simultaneous Multi-Threaded Processors, Chip Multi-Threaded Processors, to name a few.
The three techniques proposed in this thesis leverage underlying hardware features like low power functional units, drowsy caches and split data caches. These techniques reduce power consumption of a wide range of benchmarks with low performance loss.
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Chang, Shujye y 張述傑. "An Energy-Aware Link Scheduling Algorithm to Maximize Relay Nodes Life Cycle on IEEE 802.16e Mesh Networks". Thesis, 2011. http://ndltd.ncl.edu.tw/handle/83254868245276440068.
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碩士國立中正大學
資訊工程研究所
99
The IEEE 802.16 standard is defined to meet the high-speed and wide-range data transmission in an efficient way. The purpose of this thesis is to study how to minimize the energy consumption of mobile stations so as to maximize the network lifetime. We consider the real-time connections and focus on the resource scheduling which includes time slots allocation, QoS guarantee of real-time flows, interference-free on each link, and spectral reuse for the channel. The proposed energy-aware link scheduling algorithms construct a mathematical model of the energy consumption problem and provide a computationally efficient scheme to solve the problem. Comparing with traditional algorithm for real-time flows, simulation results show that the proposed scheme significantly improves the life cycle of mobile stations.
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Xuan-DeWu y 吳炫德. "Fast and Energy-Aware Inter-Task and Voltage Scheduling considering Time Penalty of Frequency Switch and Data transmission for Real Time Homogeneous Multi-Processor Systems". Thesis, 2011. http://ndltd.ncl.edu.tw/handle/09628661092019973620.
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