Rozprawy doktorskie na temat „Load sharing, Energy balancing”

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.

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.

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 données
The 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

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-complet
This 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

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.

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.

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.

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.

This thesis focuses on the development of a low power energy harvesting system specifically targeted for wireless sensor nodes (WSN) and wireless body area network (WBAN) applications. The idea for the system is derived from the operation of a micro-grid and therefore is termed as a pico-grid and it is capable of simultaneously delivering power from multiple and multitype energy harvesters to the load at the same time, through the proposed parallel load sharing mechanism achieved by a voltage droop control method. Solar panels and thermoelectric generator (TEG) are demonstrated as the main energy harvesters for the system. Since the magnitude of the output power of the harvesters is time-varying, the droop gain in the droop feedback circuitry should be designed to be dynamic and self-adjusted according to this variation. This ensures that the maximum power is capable to be delivered to the load at all times. To achieve this, the droop gain is integrated with a light dependent resistor (LDR) and thermistor whose resistance varies with the magnitude of the source of energy for the solar panel and TEG, respectively. The experimental results demonstrate a successful variation droop mechanism and all connected sources are able to share equal load demands between them, with a maximum load sharing error of 5 %. The same mechanism is also demonstrated to work for maximum power point tracking (MPPT) functionality. This concept can potentially be extended to any other types of energy harvester. The integration of energy storage elements becomes a necessity in the pico-grid, in order to support the intermittent and sporadic nature of the output power for the harvesters. A rechargeable battery and supercapacitor are integrated in the system, and each is accurately designed to be charged when the loading in the system is low and discharged when the loading in the system is high. The dc bus voltage which indicates the magnitude of the loading in the system is utilised as the signal for the desired mode of operation. The constructed system demonstrates a successful operation of charging and discharging at specific levels of loading in the system. The system is then integrated and the first wearable prototype of the pico-grid is built and tested. A successful operation of the prototype is demonstrated and the load demand is shared equally between the source converters and energy storage. Furthermore, the pico-grid is shown to possess an inherent plug-and-play capability for the source and load converters. Few recommendations are presented in order to further improve the feasibility and reliability of the prototype for real world applications. Next, due to the opportunity of working with a new semiconductor compound and accessibility to the fabrication facilities, a ZnON thin film diode is fabricated and intended to be implemented as a flexible rectifier circuit. The fabrication process can be done at low temperature, hence opening up the possibility of depositing the device on a flexible substrate. From the temperature dependent I-V measurements, a novel method of extracting important parameters such as ideality factor, barrier height, and series resistance of the diode based on a curve fitting method is proposed. It is determined that the ideality factor of the fabricated diode is high (> 2 at RT), due to the existence of other transport mechanism apart from thermionic emission that dominates the conduction process at lower temperature. It is concluded that the high series resistance of the fabricated diode (3.8 kΩ at RT) would mainly hinder the performance of the diode in a rectifier circuit.

This thesis studies the area of virtualization. The focus is on the sub-area live migration, a technique that allows a seamless migration of a virtual machine from one physical machine to another physical machine. Virtualization is an attractive technique, utilized in large computer systems, for example data centers. By using live migration, data center administrators can migrate virtual machines, seamlessly, without the users of the virtual machines taking notice about the migrations. Manually initiated migrations can become cumbersome, with an ever-increasing number of physical machines. The number of physical and virtual machines is not the only problem, deciding when to migrate and where to migrate are other problems that needs to be solved. Manually initiated migrations can also be inaccurate and untimely. Two different strategies for automated live migration have been developed in this thesis. The Push and the Pull strategies. The Push strategy tries to get rid of virtual machines and the Pull strategy tries to steal virtual machines. Both of these strategies, their design and implementation, are presented in the thesis. The strategies utilizes Shannon's Information Entropy to measure the balance in the system. The strategies further utilizes a cost model to predict the time a migration would require. This is used together with the Information Entropy to decide which virtual machine to migrate if and when a hotspot occurs. The implementation was done with the help of OMNeT++, an open-source simulation tool. The strategies are evaluated with the help of a set of simulations. These simulations include a variety of scenarios with different workloads. Our results shows that the developed strategies can re-balance a system of computers, after a large amount of virtual machines has been added or removed, in only 4-5 minutes. The results further shows that our strategies are able to keep the system balanced when the system load is at medium. This while virtual machines are continuously added or removed from the system. The contribution this thesis brings to the field is a model for how automated live migration of virtual machines can be done to improve the performance of a computer system, for example a data center.

Ce travail a pour but d'améliorer l'efficacité énergétique des réseaux de cœur en éteignant un sous-ensemble de liens par une approche SDN (Software Defined Network). Nous nous différencions des nombreux travaux de ce domaine par une réactivité accrue aux variations des conditions réseaux. Cela a été rendu possible grâce à une complexité calculatoire réduite et une attention particulière au surcoût induit par les échanges de données. Pour valider les solutions proposées, nous les avons testées sur une plateforme spécialement construite à cet effet.Dans la première partie de cette thèse, nous présentons l'architecture logicielle ``SegmenT Routing based Energy Efficient Traffic Engineering'' (STREETE). Le cœur de la solution repose sur un re-routage dynamique du trafic en fonction de la charge du réseau dans le but d'éteindre certains liens peu utilisés. Cette solution utilise des algorithmes de graphes dynamiques pour réduire la complexité calculatoire et atteindre des temps de calcul de l'ordre des millisecondes sur un réseau de 50 nœuds. Nos solutions ont aussi été validées sur une plateforme de test comprenant le contrôleur SDN ONOS et des commutateurs OpenFlow. Nous comparons nos algorithmes aux solutions optimales obtenues grâce à des techniques de programmation linéaires en nombres entiers et montrons que le nombre de liens allumés peut être efficacement réduit pour diminuer la consommation électrique tout en évitant de surcharger le réseau.Dans la deuxième partie de cette thèse, nous cherchons à améliorer la performance de STREETE dans le cas d’une forte charge, qui ne peut pas être écoulée par le réseau si des algorithmes de routages à plus courts chemins sont utilisés. Nous analysons des méthodes d'équilibrage de charge pour obtenir un placement presque optimal des flux dans le réseau.Dans la dernière partie, nous évaluons la combinaison des deux techniques proposées précédemment : STREETE avec équilibrage de charge. Ensuite, nous utilisons notre plateforme de test pour analyser l'impact de re-routages fréquents sur les flux TCP. Cela nous permet de donner des indications sur des améliorations à prendre en compte afin d'éviter des instabilités causées par des basculements incontrôlés des flux réseau entre des chemins alternatifs. Nous croyons à l'importance de fournir des résultats reproductibles à la communauté scientifique. Ainsi, une grande partie des résultats présentés dans cette thèse peuvent être facilement reproduits à l'aide des instructions et logiciels fournis
This work seeks to improve the energy efficiency of backbone networks by automatically managing the paths of network flows to reduce the over-provisioning. Compared to numerous works in this field, we stand out by focusing on low computational complexity and smooth deployment of the proposed solution in the context of Software Defined Networks (SDN). To ensure that we meet these requirements, we validate the proposed solutions on a network testbed built for this purpose. Moreover, we believe that it is indispensable for the research community in computer science to improve the reproducibility of experiments. Thus, one can reproduce most of the results presented in this thesis by following a couple of simple steps. In the first part of this thesis, we present a framework for putting links and line cards into sleep mode during off-peak periods and rapidly bringing them back on when more network capacity is needed. The solution, which we term ``SegmenT Routing based Energy Efficient Traffic Engineering'' (STREETE), was implemented using state-of-art dynamic graph algorithms. STREETE achieves execution times of tens of milliseconds on a 50-node network. The approach was also validated on a testbed using the ONOS SDN controller along with OpenFlow switches. We compared our algorithm against optimal solutions obtained via a Mixed Integer Linear Programming (MILP) model to demonstrate that it can effectively prevent network congestion, avoid turning-on unneeded links, and provide excellent energy-efficiency. The second part of this thesis studies solutions for maximizing the utilization of existing components to extend the STREETE framework to workloads that are not very well handled by its original form. This includes the high network loads that cannot be routed through the network without a fine-grained management of the flows. In this part, we diverge from the shortest path routing, which is traditionally used in computer networks, and perform a particular load balancing of the network flows. In the last part of this thesis, we combine STREETE with the proposed load balancing technique and evaluate the performance of this combination both regarding turned-off links and in its ability to keep the network out of congestion. After that, we use our network testbed to evaluate the impact of our solutions on the TCP flows and provide an intuition about the additional constraints that must be considered to avoid instabilities due to traffic oscillations between multiple paths

Doutoramento em Informática
In Mobile Ad hoc NETworks (MANETs), where cooperative behaviour is mandatory, there is a high probability for some nodes to become overloaded with packet forwarding operations in order to support neighbor data exchange. This altruistic behaviour leads to an unbalanced load in the network in terms of traffic and energy consumption. In such scenarios, mobile nodes can benefit from the use of energy efficient and traffic fitting routing protocol that better suits the limited battery capacity and throughput limitation of the network. This PhD work focuses on proposing energy efficient and load balanced routing protocols for ad hoc networks. Where most of the existing routing protocols simply consider the path length metric when choosing the best route between a source and a destination node, in our proposed mechanism, nodes are able to find several routes for each pair of source and destination nodes and select the best route according to energy and traffic parameters, effectively extending the lifespan of the network. Our results show that by applying this novel mechanism, current flat ad hoc routing protocols can achieve higher energy efficiency and load balancing. Also, due to the broadcast nature of the wireless channels in ad hoc networks, other technique such as Network Coding (NC) looks promising for energy efficiency. NC can reduce the number of transmissions, number of re-transmissions, and increase the data transfer rate that directly translates to energy efficiency. However, due to the need to access foreign nodes for coding and forwarding packets, NC needs a mitigation technique against unauthorized accesses and packet corruption. Therefore, we proposed different mechanisms for handling these security attacks by, in particular by serially concatenating codes to support reliability in ad hoc network. As a solution to this problem, we explored a new security framework that proposes an additional degree of protection against eavesdropping attackers based on using concatenated encoding. Therefore, malicious intermediate nodes will find it computationally intractable to decode the transitive packets. We also adopted another code that uses Luby Transform (LT) as a pre-coding code for NC. Primarily being designed for security applications, this code enables the sink nodes to recover corrupted packets even in the presence of byzantine attacks.
Nas redes móveis ad hoc (MANETs), onde o comportamento cooperativo é obrigatório, existe uma elevada probabilidade de alguns nós ficarem sobrecarregados nas operações de encaminhamento de pacotes no apoio à troca de dados com nós vizinhos. Este comportamento altruísta leva a uma sobrecarga desequilibrada em termos de tráfego e de consumo de energia. Nestes cenários, os nós móveis poderão beneficiar do uso da eficiência energética e de protocolo de encaminhamento de tráfego que melhor se adapte à sua capacidade limitada da bateria e velocidade de processamento. Este trabalho de doutoramento centra-se em propor um uso eficiente da energia e protocolos de encaminhamento para balanceamento de carga nas redes ad hoc. Actualmente a maioria dos protocolos de encaminhamento existentes considera simplesmente a métrica da extensão do caminho, ou seja o número de nós, para a escolha da melhor rota entre fonte (S) e um nó de destino (D); no mecanismo aqui proposto os nós são capazes de encontrar várias rotas por cada par de nós de origem e destino e seleccionar o melhor caminho segundo a energia e parâmetros de tráfego, aumentando o tempo de vida útil da rede. Os nossos resultados mostram que pela aplicação deste novo mecanismo, os protocolos de encaminhamento ad hoc actuais podem alcançar uma maior eficiência energética e balanceamento de carga. Para além disso, devido à natureza de difusão dos canais sem fio em redes ad-hoc, outras técnicas, tais como a Codificação de Rede (NC), parecem ser também promissoras para a eficiência energética. NC pode reduzir o número de transmissões, e número de retransmissões e aumentar a taxa de transferência de dados traduzindo-se directamente na melhoria da eficiência energética. No entanto, devido ao acesso dos nós intermediários aos pacotes em trânsito e sua codificação, NC necessita de uma técnica que limite as acessos não autorizados e a corrupção dos pacotes. Explorou-se o mecanismo de forma a oferecer um novo método de segurança que propõe um grau adicional de protecção contra ataques e invasões. Por conseguinte, os nós intermediários mal-intencionados irão encontrar pacotes em trânsito computacionalmente intratáveis em termos de descodificação. Adoptou-se também outro código que usa Luby Transform (LT) como um código de précodificação no NC. Projectado inicialmente para aplicações de segurança, este código permite que os nós de destino recuperem pacotes corrompidos mesmo em presença de ataques bizantinos.

Research has shown that three-phase balancing alone can improve the operation of secondary distribution networks and that the addition of energy storage to the phase balancing power electronics further helps to alleviate the negative effects of phase unbalances. However, less attention has been paid to the economic potential of said technologies and particularly for loadside implementation. It appears that the deployment of phase balancers, with or without energy storage, is indeed hampered by uncertainty related to its economic feasibility, despite both technologies being commercially available. This thesis therefore aims to assess and compare the economic feasibility of the two configurations for peak shaving purposes in the context of residential property loads in Sweden. The assessment was performed using a specially developed deterministic techno-economic model taking into consideration historical load data from three Swedish real estate, cost estimations for a range of alternatives used when sizing the systems, applicable tariffs and fees for electricity and its distribution as well as technical parameters such as the capacities and efficiencies of the involved components. A novel approach was taken by linearly extrapolating the three load profiles into three sets of 91 synthesized load profiles to enable a larger dataset for analysis. The net present values generated for each set were then graphed and analyzed per original real estate. The results showed that both configurations can be economically feasible, but only under certain conditions. A phase balancer alone was found to be feasible for real estate whose peak currents are distinctly unbalanced and exceed 50 A, with the best expected rate of return for profiles exceeding 63 A since they enable a tariff switch. The combined system was found to be even more contingent on the tariff switch and therefore only feasible for peaks above 63 A. A substantial difference in the initial investment further makes the single phase balancer the preferred choice, unless the discount rate is as low as 2 % or less. On this basis, potential investors need to assess the state of unbalance of their loads and perform their own calculation based their load profile, cost of capital and applicable tariffs.
Tidigare forskning har visat att fasbalansering enskilt kan förbättra driften hos lokala distributionsnät och att ett batterisystem i tillägg till fasbalanserarens kraftelektronik ytterligare kan minska de negativa effekterna av fasobalanser. Däremot har mindre uppmärksamhet riktats mot den ekonomiska genomförbarheten hos dessa teknologier och i synnerhet för implementation på lastens sida av elmätaren. Det tycks vara så att spridningen av fasbalanserare, med eller utan energilagring, hindras av osäkerheten kring dess ekonomiska potential trots att båda teknologierna är kommersiellt tillgängliga. Detta arbete ämnar därför att värdera och jämföra den ekonomiska nyttan hos de två konfigurationerna vid toppreducering av fastighetselen i svenska bostadsfastigheter. Värderingen utfördes med hjälp av en särskilt utvecklad deterministisk tekno-ekonomisk modell som beaktade historiska lastdata från tre svenska fastigheter, kostnadsuppskattningar för en uppsättning av konfigurationer som användes vid dimensionering av systemen, applicerbara tariffer och avgifter för elektricitet och dess distribution samt tekniska parametrar såsom kapaciteter och verkningsgrader för de olika komponenterna. Ett annorlunda tillvägagångssätt tillämpades vidare för att utöka datamängden genom linjär extrapolation av lastprofilerna, vilket resulterade i tre uppsättningar av 91 syntetiserade lastprofiler. Nettonuvärdet beräknades följaktligen för varje profil och investeringsalternativ för att sedan plottas och analyseras per ursprunglig fastighet. Resultaten visade att båda konfigurationerna kan uppvisa lönsamhet, men endast under särskilda förutsättningar. Den enskilda fasbalanseraren bedömdes som lönsam för fastigheter vars strömtoppar är påtagligt obalanserade och som överstiger 50 A, med största möjliga lönsamhet för profiler som överstiger 63 A då dessa möjliggör ett tariffbyte. Det kombinerade systemets lönsamhet bedömdes vara ännu mer beroende av tariffbytet och därför endast lönsamt för strömtoppar över 63 A. En betydligt större grundinvestering för det kombinerade systemet gör vidare att den enskilda fasbalanseraren i regel är att föredra, såvida inte kalkylräntan är så låg som 2 % eller mindre. Baserat på detta uppmanas potentiella investerare att undersöka balanstillståndet hos deras laster och att utföra en egen kalkyl baserat på deras specifika last, kapitalkostnad och nätföretag.

I takt med nya innovationer och samhällets fortsatta utveckling och utbredning ökar även elektrifieringen. För att uppnå flera av de miljömål som satts upp av Sveriges riksdag krävs en övergång till ett elsystem byggt på el från förnybara källor. Den ökande elektrifieringen medför inte bara ökade krav på den mängd el som produceras, men även förmågan att transportera den. Den ökade belastningen på elnätet skapar flaskhalsar och kapacitetsbrist i större städer och regioner, vilket gör det svårt att till exempel etablera nya fabriker och bostadsområden vilket bromsar samhällets utveckling. För att lösa denna kapacitetsbrist behövs det svenska stamnätet byggas ut. Detta är dock en relativt långsam process vilket ställer krav på innovativa lösningar som kan avlasta elnätet på kort och lång sikt. En sådan lösning är en ökad efterfrågeflexibilitet, vilket innebär att vissa effektkrävande aktiviteter flyttas till tider på dygnet då elnätet är mindre belastat. Genom att använda sig av smart elnätsteknik kan konsumenter få information om elpriser i realtid och därmed anpassa sin elkonsumtion och dra nytta av lägre elpriser och större tillgång till grön el då topplasten på elnätet är lägre. Syftet med denna studie är att undersöka hur sådana smarta elnätstjänster kan resultera i en ökad efterfrågeflexibilitet i bostäder, och om denna efterfrågeflexibilitet kan hjälpa till att motverka kapacitetsbristen i det svenska elnätet. För att undersöka detta har en litteraturstudie med fokus på beteendeförändringar kopplade till hållbar utveckling samt fyra kvalitativa intervjuer av relevanta aktörer i elbranschen gjorts. Resultaten från litteraturstudien har analyserats i syfte att undersöka huruvida de är applicerbara på smarta elnätstjänster för att uppnå en ökad efterfrågeflexibilitet eller ej. De kvalitativa intervjuerna har summerats och analyserats för att undersöka vilka frågor det råder enighet samt oenighet i bland branschens aktörer. Efter analys samt diskussionen visar studien att smarta elnätstjänster kopplade till bostäders elkonsumtion har potential att uppnå en ökad efterfrågeflexibilitet samt att denna efterfrågeflexibilitet kan bidra till att minska kapacitetsbristen i elnätet. Detta ska dock inte ses som en universell lösning utan en av flera nödvändiga lösningar för att rå på problemet.
As innovation and society continue their growth, electrification is increasing rapidly. To achieve several of the environmental goals set by the Swedish Parliament, a transition to an electricity system based on electricity from renewable sources is also required. The increasing electrification entails not only increased demands on the amount of electricity produced, but also the ability to transport it. Increased load on the electricity grid creates bottlenecks and capacity shortages in larger cities and regions, which makes it difficult to establish, among other things, new factories and residential areas, which slows down the development of society. To solve this capacity shortage, the Swedish electrical grid needs to be expanded. However, this is a relatively slow process, which places demands on innovative solutions that can relieve the electricity grid, both short term and long term. Such a solution is an increased demand flexibility, which means that certain power-demanding activities are moved to times of the day when the grid is less congested. By using smart grid technology, consumers can get information about electricity prices in real time and thereby adjust their electricity consumption and benefit from lower electricity prices and greater access to renewable energy when the top load on the electricity grid is lower. The purpose of this study is to investigate how such smart grid services can result in increased demand flexibility in homes, and whether this demand flexibility can help counteract the capacity shortage in the Swedish grid. To investigate this, a literature study focusing on behavioral changes linked to sustainable development, and four qualitative interviews with relevant actors in the energy industry, have been conducted. The results from the literature study have been analyzed to investigate whether or not they are applicable to smart grid services to achieve increased demand flexibility. The qualitative interviews have been summarized and analyzed to examine what issues there is agreement and disagreement in among the industry's players. After analysis and discussion, the study shows that smart grid services linked to residential electricity consumption have the potential to achieve increased demand flexibility and that this demand flexibility can contribute to reducing capacity shortage. However, this should not be seen as a universal solution but as one of several necessary solutions to tackle the problem.

Дисертація на здобуття наукового ступеню кандидата технічних наук за спеціальністю 05.14.02 – електричні станції, мережі і системи – Національний технічний університет "Харківський політехнічний інститут", Харків, 2018. Дисертаційна робота присвячена регулюванню графіків електричного навантаження за допомогою споживачів-регуляторів з підключення у їх систему електропостачання кінетичного енергонакопичувача, що призведе до підвищення ефективності функціонування електричних мереж та показників якості електроенергії. У дисертаційній роботі досліджені методи регулювання графіків електронавантаження та обґрунтована доцільність використання адміністративних будівель з акумулючими пристроями, підключеними до системи електропостачання, у якості споживачів – регуляторів. Досліджено застосування різних типів акумулюючих пристроїв у системах електропостачання, та запропоновано використання кінетичного енергонакопичувача для регулювання графіків навантаження споживача регулятора. Проведено аналіз методів оцінки ризиків в енергетиці з метою їх зниження, що призведе до підвищення надійності роботи системи електропостачання споживача-регулятора та застосовано метод ієрархій Т. Сааті безпосередньо для аналізу ризиків та їх компенсації при підключені у систему електропостачання кінетичного енергонакопичувача. Розроблено конструкцію маховика з змінним моментом інерції та дисбалансними вантажами, який має кращі технічні характеристики у порівнянні з аналогами та може бути застосований у складі кінетичного енергонакопичувача. Розроблений спосіб симетрування навантаження у системі електропостачання адміністративної будівлі, заснований на використанні кінетичного енергонакопичувача. Розроблена модель обміну енергією між системою електропостачання будівлі та кінетичним енергонакопичувачем. Показана можливість регулювання графіків електронавантаження споживача-регулятора при регулюванні параметрів та характеристик кінетичного енергонакопичувача.
Thesis for the degree of candidate of technical sciences in specialty 141 – electric power industry, electrical engineering and electromechanics – National Technical University "Kharkov Polytechnic Institute" of the Ministry of Education and Science of Ukraine, Kharkov, 2018. The thesis is devoted to regulation of electric load schedules with the help of regulator consumers to connect kinetic energy storages to their power supply system, which will lead to an increase in the efficiency of the functioning of electrical networks and power quality indicators. In the dissertation the methods of regulation of electronic loading schedules are investigated and the feasibility of using administrative buildings with storage devices connected to the power supply system, as consumers of regulators, is substantiated. The application of different types of accumulating devices in power supply systems has been investigated, and the use of a kinetic energy carrier for regulating load schedules of the consumer-regulator has been proposed. The analysis of risk assessment methods in energy with the purpose of their reduction, which will increase the reliability of the power supply system of the consumer-regulator, and the method of the hierarchy of T.Saati is used directly for the analysis of risks and their compensation when connected to the system of power supply of the kinetic energy accumulator. The design of the flywheel with a variable torque of inertia and imbalance loads, which differs from the existing presence of alternating moment of inertia and imbalance loads, which will reduce the energy consumption in the initial period of rotation of the flywheel and improve the smoothness of rotation in the working mode is developed, therefore, it has the best technical characteristics compared with analogues and can be used as a kinetic energy storage device. The method of balancing the load in the power supply system of an administrative building, based on the use of kinetic energy storage, has allowed to improve the quality of electricity due to the lack of switching in the power supply system. A model for energy exchange between the power supply system of the building and the kinetic energy storage device is developed, which differs from the current taking into account the design of the flywheel KES, which makes it possible to improve the accuracy of energy calculations. The possibility of regulating the electric load graphs of the consumer-regulator is shown when adjusting the parameters and characteristics of the kinetic energy storage, which will effectively regulate the load schedule of the electrical network as a whole. The influence of the design of the electric motor and the flywheel structure in the KEN on the accumulation of electric energy on the acceleration and loading characteristics of the drive for controlling the electric load schedule of the electric networks has been experimentally confirmed.

Дисертаційна робота присвячена регулюванню графіків електричного навантаження за допомогою споживачів-регуляторів з підключення у їх систему електропостачання кінетичного енергонакопичувача, що призведе до підвищення ефективності функціонування електричних мереж та показників якості електроенергії. У дисертаційній роботі досліджені методи регулювання графіків електронавантаження та обґрунтована доцільність використання адміністративних будівель з акумулючими пристроями, підключеними до системи електропостачання, у якості споживачів – регуляторів. Досліджено застосування різних типів акумулюючих пристроїв у системах електропостачання, та запропоновано використання кінетичного енергонакопичувача для регулювання графіків навантаження споживача регулятора. Проведено аналіз методів оцінки ризиків в енергетиці з метою їх зниження, що призведе до підвищення надійності роботи системи електропостачання споживача-регулятора та застосовано метод ієрархій Т.Сааті безпосередньо для аналізу ризиків та їх компенсації при підключені у систему електропостачання кінетичного енергонакопичувача. Розроблено конструкцію маховика з змінним моментом інерції та дисбалансними вантажами, який має кращі технічні характеристики у порівнянні з аналогами та може бути застосований у складі кінетичного енергонакопичувача. Розроблений спосіб симетрування навантаження у системі електропостачання адміністративної будівлі, заснований на використанні кінетичного енергонакопичувача. Розроблена модель обміну енергією між системою електропостачання будівлі та кінетичним енергонакопичувачем. Показана можливість регулювання графіків електронавантаження споживача-регулятора при регулюванні параметрів та характеристик кінетичного енергонакопичувача.
The thesis is devoted to regulation of electric load schedules with the help of regulator consumers to connect kinetic energy storages to their power supply system, which will lead to an increase in the efficiency of the functioning of electrical networks and power quality indicators. In the dissertation the methods of regulation of electronic loading schedules are investigated and the feasibility of using administrative buildings with storage devices connected to the power supply system, as consumers of regulators, is substantiated. The application of different types of accumulating devices in power supply systems has been investigated, and the use of a kinetic energy carrier for regulating load schedules of the consumer-regulator has been proposed. The analysis of risk assessment methods in energy with the purpose of their reduction, which will increase the reliability of the power supply system of the consumer-regulator, and the method of the hierarchy of T.Saati is used directly for the analysis of risks and their compensation when connected to the system of power supply of the kinetic energy accumulator. The design of the flywheel with a variable torque of inertia and imbalance loads, which differs from the existing presence of alternating moment of inertia and imbalance loads, which will reduce the energy consumption in the initial period of rotation of the flywheel and improve the smoothness of rotation in the working mode is developed, therefore, it has the best technical characteristics compared with analogues and can be used as a kinetic energy storage device. The method of balancing the load in the power supply system of an administrative building, based on the use of kinetic energy storage, has allowed to improve the quality of electricity due to the lack of switching in the power supply system. A model for energy exchange between the power supply system of the building and the kinetic energy storage device is developed, which differs from the current taking into account the design of the flywheel KES, which makes it possible to improve the accuracy of energy calculations. The possibility of regulating the electric load graphs of the consumer-regulator is shown when adjusting the parameters and characteristics of the kinetic energy storage, which will effectively regulate the load schedule of the electrical network as a whole. The influence of the design of the electric motor and the flywheel structure in the KEN on the accumulation of electric energy on the acceleration and loading characteristics of the drive for controlling the electric load schedule of the electric networks has been experimentally confirmed.

Energy consumption is a major concern in Wireless Sensor Networks (WSNs) resulting in a strong demand for energy-aware communication technologies. In this context, several unequal cluster-based routing protocols have been proposed. However, few of them adopt energetic analysis models for the calculation of the optimal cluster radius and several protocols can not realize an optimal workload balance between sensor nodes. In this scope, the aim of the dissertation is to develop a cluster-based routing protocol for improving energy efficiency in WSN. We propose a Fuzzy-based Energy-Aware Unequal Clustering algorithm (FEAUC) with circular partitioning to balance the energy consumption between sensor nodes and solve the hotspot problem created by a multi-hop communication. The developed FEAUC involves mainly four phases: An off-line phase, a cluster formation phase, a cooperation phase and data collection phase. During the off-line phase, an energy analysis is performed to calculate the radius of each ring and the optimal cluster radius per ring. The cluster formation phase is based on a fuzzy logic approach for the cluster head (CH) selection. The cooperation phase aims to define an intermediate node as a router between different CHs. While, in the data collection phase, transmitting data packet from sensor nodes to their appropriate CHs is defined as an intra-cluster communication, and transmitting data from one CH to another until reaching the base station, is defined as an inter-cluster communication. The feasibility of the developed FEAUC is demonstrated by elaborating comparison with selected referred unequal clustering algorithms considering different parameters, mainly, the energy consumption, battery lifetime, time to first node shuts down (FND), time of half of nodes off-line (HND) and time to last node dies (LND). Although, the developed FEAUC is intended to enhance the network lifetime by distributing the large load of CH tasks equally among the normal nodes, running the clustering process in each round is an additional burden, which can significantly drain the remaining energy. For this reason, the FEAUC based protocol has been further developed to become a fault tolerant algorithm (FEAUC-FT). It supports the fault tolerance by using backup CHs to avoid the re-clustering process in certain rounds or by building further routing paths in case of a link failure between different CHs. The validation of the developed FEAUC in real scenarios has been performed. Some sensor nodes, powered with batteries, are deployed in a circular area forming clusters. Performance evaluations are carried out by realistic scenarios and tested for a real deployment using the low-power wireless sensor node panStamp. To complete previous works, as a step of proof of concept, a smart irrigation system is designed, called Air-IoT. Furthermore, a real-time IoT-based sensor node architecture to control the quantity of water in some deployed nodes is introduced. To this end, a cloud-connected wireless network to monitor the soil moisture and temperature is well-designed. Generally, this step is essential to validate and evaluate the proposed unequal cluster-based routing algorithm in a real demonstrator. The proposed prototype guarantees both real-time monitoring and reliable and cost-effective transmission between each node and the base station.:1 Introduction 2 Theoretical background 3 State of the art of unequal cluster-based routing protocols 4 FEAUC: Fuzzy-based Energy-Aware Unequal Clustering 5 Experimental validation of the developed unequal clustering protocol 6 Real application to specific uses cases 7 Conclusions and future research directions
Der Energieverbrauch ist ein Hauptanliegen in drahtlosen Sensornetzwerken (WSNs), was zu einer starken Nachfrage nach energiebewussten Kommunikationstechnologien führt. In diesem Zusammenhang wurden mehrere ungleiche clusterbasierte Routing-Protokolle vorgeschlagen. Allerdings verwenden nur die wenigsten energetische Analysemodelle für die Berechnung des optimalen Cluster-Radius, und mehrere Protokolle können keine optimale Auslastungsbalance zwischen Sensorknoten realisieren. In diesem Zusammenhang ist es das Ziel der Dissertation, ein clusterbasiertes Routing-Protokoll zur Verbesserung der Energieeffizienz im WSN zu entwickeln. Wir schlagen einen Fuzzy-basierten Energy-Aware Unequal Clustering-Algorithmus (FEAUC) mit zirkulärer Partitionierung vor, um den Energieverbrauch zwischen Sensorknoten auszugleichen und das durch eine Multi-Hop-Kommunikation entstehende Hotspot-Problem zu lösen. Der entwickelte FEAUC umfasst hauptsächlich vier Phasen: Eine Offline-Phase, eine Clusterbildungsphase, eine Kooperationsphase und eine Phase der Datensammlung. Während der Offline-Phase wird eine Energieanalyse durchgeführt, um den Radius jedes Ringes und den optimalen Cluster- Radius pro Ring zu berechnen. Die Clusterbildungsphase basiert auf einem Fuzzy-Logik-Ansatz für die Clusterkopf (CH)-Auswahl. Die Kooperationsphase zielt darauf ab, einen Zwischenknoten als einen Router zwischen verschiedenen CHs zu definieren. In der Datensammelphase wird die Übertragung von Datenpaketen von Sensorknoten zu ihren entsprechenden CHs als eine Intra-Cluster-Kommunikation definiert, während die Übertragung von Daten von einem CH zu einem anderen CH bis zum Erreichen der Basisstation als eine Inter-Cluster-Kommunikation definiert wird. Die Machbarkeit des entwickelten FEAUC wird durch die Ausarbeitung eines Vergleichs mit ausgewählten referenzierten ungleichen Clustering-Algorithmen unter Berücksichtigung verschiedener Parameter demonstriert, hauptsächlich des Energieverbrauchs, der Batterielebensdauer, der Zeit bis zum Abschalten des ersten Knotens (FND), der Zeit, in der die Hälfte der Knoten offline ist (HND) und der Zeit bis zum letzten Knoten stirbt (LND). Obwohl mit dem entwickelten FEAUC die Lebensdauer des Netzwerks erhöht warden soll, indem die große Last der CH-Aufgaben gleichmäßig auf die übrigen Knoten verteilt wird, stellt die Durchführung des Clustering-Prozesses in jeder Runde eine zusätzliche Belastung dar, die die verbleibende Energie erheblich entziehen kann. Aus diesem Grund wurde das auf FEAUC basierende Protokoll zu einem fehlerto-leranten Algorithmus (FEAUC-FT) weiterentwickelt. Er unterstützt die Fehlerto-leranz durch die Verwendung von Backup-CHs zur Vermeidung des Re-Clustering-Prozesses in bestimmten Runden oder durch den Aufbau weiterer Routing-Pfade im Falle eines Verbindungsausfalls zwischen verschiedenen CHs. Die Validierung des entwickelten FEAUC in realen Szenarien ist durchgeführt worden. Einige Sensorknoten, die mit Batterien betrieben werden, sind in einem kreisförmigen Bereich angeordnet und bilden Cluster. Leistungsbewertungen warden anhand realistischer Szenarien durchgeführt und für einen realen Einsatz unter Verwendung des drahtlosen Low-Power-Sensorknoten panStamp getestet. Zur Vervollständigung früherer Arbeiten wird als Schritt des Proof-of-Concept ein intelligentes Bewässerungssystem mit der Bezeichnung Air-IoT entworfen. Darüber hinaus wird eine IoT-basierte Echtzeit-Sensorknotenarchitektur zur Kontrolle derWassermenge in einigen eingesetzten Knoten eingeführt. Zu diesem Zweck wird ein mit der Cloud verbundenes drahtloses Netzwerk zur Überwachung der Bodenfeuchtigkeit und -temperatur gut konzipiert. Im Allgemeinen ist dieser Schritt unerlässlich, um den vorgeschlagenen ungleichen clusterbasierten Routing-Algorithmus in einem realen Demonstrator zu validieren und zu bewerten.Der vorgeschlagene Prototyp garantiert sowohl Echtzeit-Überwachung als auch zuverlässige und kostengünstige Übertragung zwischen jedem Knoten und der Basisstation.:1 Introduction 2 Theoretical background 3 State of the art of unequal cluster-based routing protocols 4 FEAUC: Fuzzy-based Energy-Aware Unequal Clustering 5 Experimental validation of the developed unequal clustering protocol 6 Real application to specific uses cases 7 Conclusions and future research directions

Depuis 2016, il est bien connu que les réseaux mobiles dominent nos vies. Nous utilisons nos téléphones cellulaires pour presque tout: du réseautage social au streaming, à la recherche de logement ou pour les transactions bancaires. Néanmoins, il semble que les opérateurs ne comprennent pas cette domination, puisque leurs réseaux sont constitués de nœuds qui: (i) subissent d'énormes fluctuations de charge, (ii) gaspillent leurs ressources, et (iii) sont accusés d'être tueurs d'énergie majeurs. Ces inconvénients nuisent à load-balancing, efficacité spectrale et énergétique, respectivement. L'objectif de cette dissertation est d'étudier attentivement ces gains d'efficacité et d'établir un bon “trade off” entre eux pour les futurs réseaux hétérogènes 5G mobiles. Dans cette direction, nous nous concentrons tout d'abord sur (i) l'utilisateur et la différenciation du trafic, émergeant des applications de type MTC et IoT, et (ii) du RAN. Plus précisément, nous réalisons une modélisation, une analyse de performance et une optimisation appropriées pour une famille d'objectifs, en utilisant des outils provenant principalement de l'optimisation (non) convexe, de la probabilité et de la théorie des files d'attente. Après, nous soulignons que l'optimisation des fonctionnalités RAN, suivie d'un formidable « capacity crunch », posent de sérieuses contraintes dans le réseau de backhaul en le faisant apparaître comme un goulet d'étranglement de performance. Ainsi, nous incluons (iii) dans notre cadre: des contraintes de capacité de liaison de backhaul dans des topologies génériques. Enfin, nous considérons le problème de l'allocation TDD dans les réseaux d'accès et de backhaul
By 2016, it is well-known that mobile networking has dominated our lives. We use our mobile cell phones for almost everything: from social networking to streaming, finding accommodation or banking. Nevertheless, it seems that operators have not understood yet this domination, since their networks consist of nodes that: (i) suffer from enormous load fluctuations, (ii) waste their resources, and (iii) are blamed to be a major energy-killer worldwide. Such shortcomings hurt: load-balancing, spectral and energy efficiency, respectively. The goal of this dissertation is to carefully study these efficiencies and achieve a good trade-off between them for future mobile 5G heterogeneous networks (HetNets). Towards this direction, we firstly focus on (i) the user and traffic differentiation, emerging from the MTC and IoT applications, and (ii) the RAN. Specifically, we perform appropriate modeling, performance analysis and optimization for a family of objectives, using tools mostly coming from (non) convex optimization, probability and queueing theory. Our initial consideration is on network-layer optimizations (e.g. studying the user association problem). Then, we analytically show that cross-layer optimization is key for the success of future HetNets, as one needs to jointly study other problems coming from the layers below (e.g. the TDD allocation problem from the MAC, or the cross-interference management from the PHY) to avoid performance degradation. Finally, we add the backhaul network into our framework, and consider additional constraints related to the backhaul capacity, backhaul topology, as well as the problem of backhaul TDD allocation

This thesis reports on the investigations, simulations and analyses of novel power electronics topologies and control strategies. The research is financed by an Australian Research Council (ARC) Linkage (07-09) grant. Therefore, in addition to developing original research and contributing to the available knowledge of power electronics, it also contributes to the design of a DC-DC converter for specific application to the auxiliary power supply in electric trains. Specifically, in this regard, it contributes to the design of a 7.5 kW DC-DC converter for the industrial partner (Schaffler and Associates Ltd) who supported this project. As the thesis is formatted as a ‘thesis by publication’, the contents are organized around published papers. The research has resulted in eleven papers, including seven peer reviewed and published conference papers, one published journal paper, two journal papers accepted for publication and one submitted journal paper (provisionally accepted subject to few changes). In this research, several novel DC-DC converter topologies are introduced, analysed, and tested. The similarity of all of the topologies devised lies in their ‘current circulating’ switching state, which allows them to store some energy in the inductor, as extra inductor current. The stored energy may be applied to enhance the performance of the converter in the occurrence of load current or input voltage disturbances. In addition, when there is an alternating load current, the ability to store energy allows the converter to perform satisfactorily despite frequently and highly varying load current. In this research, the capability of current storage has been utilised to design topologies for specific applications, and the enhancement of the performance of the considered applications has been illustrated. The simplest DC-DC converter topology, which has a ‘current circulating’ switching state, is the Positive Buck-Boost (PBB) converter (also known as the non-inverting Buck-Boost converter). Usually, the topology of the PBB converter is operating as a Buck or a Boost converter in applications with widely varying input voltage or output reference voltage. For example, in electric railways (the application of our industrial partner), the overhead line voltage alternates from 1000VDC to 500VDC and the required regulated voltage is 600VDC. In the course of this research, our industrial partner (Schaffler and Associates Ltd) industrialized a PBB converter–the ‘Mudo converter’–operating at 7.5 kW. Programming the onboard DSP and testing the PBB converter in experimental and nominal power and voltage was part of this research program. In the earlier stages of this research, the advantages and drawbacks of utilization of the ‘current circulating’ switching state in the positive Buck-Boost converter were investigated. In brief, the advantages were found to be robustness against input voltage and current load disturbances, and the drawback was extra conduction and switching loss. Although the robustness against disturbances is desirable for many applications, the price of energy loss must be minimized to attract attention to the utilization of the PBB converter. In further stages of this research, two novel control strategies for different applications were devised to minimise the extra energy loss while the advantages of the positive Buck-Boost converter were fully utilized. The first strategy is Smart Load Controller (SLC) for applications with pre-knowledge or predictability of input voltage and/or load current disturbances. A convenient example of these applications is electric/hybrid cars where a master controller commands all changes in loads and voltage sources. Therefore, the master controller has a pre-knowledge of the load and input voltage disturbances so it can apply the SLC strategy to utilize robustness of the PBB converter. Another strategy aiming to minimise energy loss and maximise the robustness in the face of disturbance is developed to cover applications with unexpected disturbances. This strategy is named Dynamic Hysteresis Band (DHB), and is used to manipulate the hysteresis band height after occurrence of disturbance to reduce dynamics of the output voltage. When no disturbance has occurred, the PBB converter works with minimum inductor current and minimum energy loss. New topologies based on the PBB converter have been introduced to address input voltage disturbances for different onboard applications. The research shows that the performance of applications of symmetrical/asymmetrical multi-level diode-clamped inverters, DC-networks, and linear-assisted RF amplifiers may be enhanced by the utilization of topologies based on the PBB converter. Multi-level diode-clamped inverters have the problem of DC-link voltage balancing when the power factor of their load closes to unity. This research has shown that this problem may be solved with a suitable multi-output DC-DC converter supplying DClink capacitors. Furthermore, the multi-level diode-clamped inverters supplied with asymmetrical DC-link voltages may improve the quality of load voltage and reduce the level of Electromagnetic Interference (EMI). Mathematical analyses and experiments on supplying symmetrical and asymmetrical multi-level inverters by specifically designed multi-output DC-DC converters have been reported in two journal papers. Another application in which the system performance can be improved by utilization of the ‘current circulating’ switching state is linear-assisted RF amplifiers in communicational receivers. The concept of ‘linear-assisted’ is to divide the signal into two frequency domains: low frequency, which should be amplified by a switching circuit; and the high frequency domain, which should be amplified by a linear amplifier. The objective is to minimize the overall power loss. This research suggests using the current storage capacity of a PBB based converter to increase its bandwidth, and to increase the domain of the switching converter. The PBB converter addresses the industrial demand for a DC-DC converter for the application of auxiliary power supply of a typical electric train. However, after testing the industrial prototype of the PBB converter, there were some voltage and current spikes because of switching. To attenuate this problem without significantly increasing the switching loss, the idea of Active Gate Signalling (AGS) is presented. AGS suggests a smart gate driver that selectively controls the switching process to reduce voltage/current spikes, without unacceptable reduction in the efficiency of switching.

碩士
國立交通大學
資訊科學與工程研究所
99
Recent movement in cloud computing is showing the trend that more and more companies start to deploy their services on the cloud instead of worrying about the troublesome server configuration and administration by themselves. This trend also helps in consolidating hardware resource usage because the same set of machine resources can serve multiple companies. Through a virtualization technique, different companies’ virtual machines (VMs) could share hardware resources on a single physical machine to improve the resource utilization. In order to maximize resource utilization, a load-balancing mechanism for cloud computing is needed to avoid performance degradation, hardware error or failure due to some overloading physical machines. Load balancing for cloud computing can be performed by migrating a VM from an overloaded host to an underutilized host. Since VM migration time are proportional to the amount of physical memory allocated to the VM. In a cloud data center with tens of thousands of physical machines and hundreds of thousands of VMs, one by one VM migration may take long time to reach a system load equilibrium state. In this paper, we propose an algorithm that transforms the load-balancing problem into a minimum weighted matching problem of a weighted bipartite graph. According to the minimum weighted matching obtained from Hungarian method, we concurrently migrate VMs from overloaded hosts to underutilized hosts. We use the CloudSim toolkit to test our algorithm’s performance and the experimental results show that our algorithm not only obtains a good load balance but also reduces the time to reach system load equilibrium state. We also build a cloud development platform via XCP OS to prove that our algorithm could be used in a realistic cloud environment. Furthermore, a major cause of energy inefficiency in a cloud datacenter is the idle power wasted when servers run at low utilization. Therefore, we modify our load-balancing algorithm to migrate all VMs out of low utilized hosts, then to turn off them to save energy during load-balancing process.

碩士
國立交通大學
網路工程研究所
103
Unlike the traditional network, the Software Defined Network (SDN) provides a way to control flows in a network by decoupling the control plane and data plane. Since an SDN network using a single controller to manage flows in the network may lead to SDN scalability and a single point of failure problems, some related work puts an emphasis on the issues of distributed SDN controllers. A related work on distributed SDN controllers or multiple SDN controllers, EstiCon, proposed a dynamic load balancing scheme. However, the issue of energy saving for distributed SDN controllers hasn’t been addressed. The main contributions of this paper are as follows. (1) We propose an Energy-Aware Load Balancing (EALB) algorithm for distributed SDN controllers. The proposed EALB balances the loads of distributed SDN controllers and turns some controllers into sleep mode under light load. The loads of SDN controllers are mainly caused by number of packet-in messages received. When packet-in messages become too many for a controller to handle, its loading needs to be migrated. When a controller becomes overloaded, the proposed EALB migrates some switches handled by the overloaded controller to other controllers in order to balance the loads. (2) In addition, we use a neural network based predictor to check whether it can turn a controller into sleep mode for energy saving. Simulation results show that the proposed EALB can save 11% of energy consumption compared to LB (EALB without energy saving). For load balancing of distributed SDN controllers, the load balancing metric (LBM) of the proposed EALB is from 1.19 to 1.4 under packet-in message rates from 300 to 900 (messages/second), which is only slightly higher than that (from 1.16 to 1.35) of LB. Keywords: Energy-aware, load balancing, neural network-based prediction, packet-in message, software defined network. Keywords: Energy-aware, Load balancing, neural network-based prediction, packet-in message, software defined network.

碩士
國立中興大學
資訊科學與工程學系
104
Unlike traditional network, software define network is divided into control plane and data plane. Controller can decide how to transfer data. We can use a switch as load-balancing switch, and we decide how to transfer packet according to rule of server to reach the target of load balance. When the load of controller is too high, it may affect performance of load balance system. Therefore, how to reduce the load of controller becomes an important issue. Wildcard Rule is the subject matter we study and improve in this thesis. We propose two methods used together, one is sharing not full server and another is exchange server rules. We use two methods at the same time to avoid reducing the utilization of server without using other server when a server is full. In the case of maintaining the utilization of server, we should reduce the rule change as far as possible to maintain original wildcard rules to reach original target. In this thesis, we use the Mininet simulator as a platform to carry out many experiments for verification. The simulation results show that the method we proposed improves by 20% of server resource utilization, when compared with the original method. Our methods perform well especially when the traffic load of specific IP increases. They can effectively reduce 50% of rule changes while maintaining the same utilization level.

碩士
輔仁大學
電機工程學系碩士班
102
Ambient energy from solar, vibration, heat and wind provide alternative energy sources to power sensors and extend the lifetime of wireless sensor networks, which have traditionally been powered by batteries. This paper aims to enhance the performance of energy harvesting powered wireless sensor networks in three aspects: relaying, scheduling, and medium access control. To better adapt to the characteristics of energy harvesting, an asynchronous receiver-initiated duty-cycling approach is preferred in energy harvesting powered wireless sensor networks. This reduces the duty cycle of senders, and regulates the duty and sleep intervals according to the energy levels of sensors. When nodes run out of power and need time to recharge, network holes or voids develop, forcing data packets to be routed via other paths, like detours. The proposed relaying strategy aims to prevent holes by balancing the load across the network according to nodes’ energy harvesting characteristics. This is a natural consequence of the asynchronous duty-cycling by scheduling transmission based on the receiver’s availability. The simulation results show that our scheme outperforms in terms of end-to-end delay, sender duty cycle, collision ratio, remaining energy, packet delivery ratio, energy fairness ratio, and de-tour ratio.

碩士
國立臺灣大學
資訊工程學研究所
97
Opportunistic routing has been widely approved because of its throughput improvement for wireless mesh networks; however, few researches focus on transforming its benefit into realizing energy efficiency for wireless sensor networks (WSNs). We notice that two common issues in fixed-path routing schemes, including single-path routing or multi-path routing, are that (1) a path may traverse through a fixed set of sensors, draining out their energy, and (2) packet retransmission over an unreliable link of any fixed-path may consume energy significantly. In this paper, we exploit two natural advantages of opportunistic routing, i.e., path diversity and the improvement of transmission reliability, to develop a distributed routing scheme (EFFORT) for prolonging the network-lifetime of a WSN. Unlike prior works on minimizing transmission delay in opportunistic routing, we propose a metric (called OEC) that assists each sensor in determining a suitable forwarding set for reducing the damage to the lifetime caused by each forwarding, and, thus, enable EFFORT to extend the network lifetime by implementing forwarder selection and relay prioritization based on OEC. Simulation results show that EFFORT achieves network-lifetime extension, as well as energy-cost minimization as compared with other routing protocols.

The paper presents a new cluster based routing algorithm that exploits the redundancy properties of the sensor networks in order to address the traditional problem of load balancing and energy efficiency in the WSNs.The algorithm makes use of the nodes in a sensor network of which area coverage is covered by the neighbours of the nodes and mark them as temporary cluster heads. The algorithm then forms two layers of multi hop communication. The bottom layer which involves intra cluster communication and the top layer which involves inter cluster communication involving the temporary cluster heads. Performance studies indicate that the proposed algorithm solves effectively the problem of load balancing and is also more efficient in terms of energy consumption from Leach and the enhanced version of Leach.

A dissertation submitted to the Faculty of Engineering and the Built Environment, University of the Witwatersrand, in ful lment of the requirements for the degree of Master of Science in Engineering. Johannesburg, 2016
This research investigates the power sharing between distributed energy resources with voltage and frequency droop control. A case study based on voltage sources in an islanded microgrid is set up in the laboratory, referred to as: The Example Microgrid. The Example Microgrid consists of two synchronous generators, active and reactive power loads. A simulation model is constructed based on the laboratory set-up, where componentwise and system-wise testing are completed. The simulation results are validated with the experimental set-up, and it is concluded that the model accurately represents the physical system under steady-state conditions. Further simulation studies on conventional droop controllers are conducted based on the Example Microgrid model. The results indicate that the use of conventional droop control is inappropriate for small, low-voltage islanded microgrids. As a possible application of this work, three variations of adapted droop controllers are simulated and their performance evaluated. It is found that with the adapted droop controllers, the power sharing error can be minimised
M T 2016

In this dissertation, we studied methods for improving efficiency and effectiveness of multipath routing in computer networks. We showed that multipath routing can improve network performance for failure recovery, load balancing, Quality of Service (QoS), and energy consumption. We presented a method for reducing the overhead of computing dynamic path metrics, one of the obstacles for implementing dynamic multipath routing in real world networks. In the first part, we proposed a method for building disjoint multipaths that could be used for local failure recovery as well as for multipath routing. Proactive failure recovery schemes have been recently proposed for continuous service of delay-sensitive applications during failure transients at the cost of extra infrastructural support in the form of routing table entries, extra addresses, etc. These extra infrastructure supports could be exploited to build alternative disjoint paths in those frameworks, while keeping the lengths of the alternative paths close to those of the primary paths. The evaluations showed that it was possible to extend the proactive failure recovery schemes to provide support for nearly-disjoint paths which could be employed in multipath routing for load balancing and QoS. In the second part, we proposed a method for reducing overhead of measuring dynamic link state information for multipath routing, specifically path delays used in Wardrop routing. Even when dynamic routing could be shown to offer convergence properties without oscillations, it has not been widely adopted. One of reasons was that the expected cost of keeping the link metrics updated at various nodes in the network. We proposed threshold-based updates to propagate the link state only when the currently measured link state differs from the last updated state consider- ably. Threshold-based updates were shown through analysis and simulations to offer bounded guarantees on path quality while significantly reducing the cost of propagating the dynamic link metric information. The simulation studies indicated that threshold based updates can reduce the number of link updates by up to 90-95% in some cases. In the third part, we proposed methods of using multipath routing for reducing energy consumption in computer networks. Two different approaches have been advocated earlier, from traffic engineering and topology control to hardware-based approaches. We proposed solutions at two different time scales. On a finer time granularity, we employed a method of forwarding through alternate paths to enable longer sleep schedules of links. The proposed schemes achieved more energy saving by increasing the usage of active links and the down time of sleeping links as well as avoiding too frequent link state changes. To the best of our knowledge, this was the first technique combining a routing scheme with hardware scheme to save energy consumption in networks. In our evaluation, alternative forwarding reduced energy consumption by 10% on top of a hardware-based sleeping scheme. On a longer time granularity, we proposed a technique that combined multipath routing with topology control. The proposed scheme achieved increased energy savings by maximizing the link utilization on a reduced topology where the number of active nodes and links are minimized. The proposed technique reduced energy consumption by an additional 17% over previous schemes with single/shortest path routing.

A reliable power is paramount and loss of power to communication equipment can mean loss of service to clients and loss of millions of dollars to industries. Also, climate is changing; greenhouse gas emissions from human activity are the major cause for global warming.