In this thesis, we develop algorithms that make optimal use of frequency scaling to schedule jobs with real??time requirements. Dynamic voltage scaling is a technique used to reduce energy consumption in wide variety of systems. Reducing supply voltage results in a lower processor clock speed since the supply voltage has a proportional dependency on the clock speed of the processing system. In hard real??time systems, unduly reducing the speed of processor could result in jobs missing their deadlines. The voltage scaling in such systems should therefore take into consideration the deadline of jobs. This thesis will address two questions: First, given a set of discrete frequency levels, we determine an energy-optimal sched- ule of a given set of real-time jobs. We model the problem as a network flow graph and use linear programming to solve the problem. The schedule can be used on processors with discrete frequencies (like Transmeta Efficeon Processor and AMD Turion 64 Processor). Second, given a set of real??time jobs, we determine a set of optimal frequency levels which minimizes the energy consumption while meeting all the timing con- straints. This can be used to model variable-capacity facilities in operations re- search, where the capacity of the facility can be controlled at a cost.

Que le phénomène découle d’une prise de conscience des conséquences sur l’environnement, d’une opportunité économique ou d’une question de réputation et de commerce, la réduction des émissions de gaz à effets de serre est récemment devenue un objectif de premier plan. Les individus, les entreprises et les gouvernements effectuent un effort important pour réduire la dépense énergétique de multiples secteurs d’activité. Parallèlement, les technologies de l’information et de la communication sont de plus en plus présentes dans la plupart des activités humaines et l’on a estimé que 2% des émissions de gaz à effets de serre pouvaient leur être attribuées, cette proportion atteignant 10 % dans les pays fortement industrialisés [1, 2]. Si ces chiffres paraissent raisonnables aujourd’hui, ils sont certainement appelés à croître à l’avenir. À l’heure du cloud computing, les infrastructures de calcul et de communication demandent de plus en plus de performance et de disponibilité et imposent l’utilisation de matériels puissants et engendrant une consommation d’énergie importante du fait de leur fonctionnement direct, mais aussi à cause du refroidissement qu’ils nécessitent. En outre, les contraintes de disponibilité imposent une conception d’architectures redondantes et dimensionnées sur une charge crête. Les infrastructures sont donc souvent sous-utilisées et adapter leur niveau de performance à la charge effectivement constatée constitue une piste d’optimisation prometteuse à divers niveaux. Si l’on adopte un strict point de vue environnemental, l’objectif du Green Networking consiste à réduire le volume d’émissions de gaz à effets de serre dues au processus de communication. L’utilisation de sources d’énergie renouvelables ou d’électronique de faible consommation (par exemple asynchrone) constituent des pistes évidentes d’amélioration. / The reduction of power consumption in communication networks has become a key issue for both the Internet Service Providers (ISP) and the research community. Ac- cording to different studies, the power consumption of Information and Communication Technologies (ICT) varies from 2% to 10% of the worldwide power consumption [1, 2]. Moreover, the expected trends for the future predict a notably increase of the ICT power consumption, doubling its value by 2020 [2] and growing to around 30% of the worldwide electricity demand by 2030 according to business-as-usual evaluation scenarios [15]. It is therefore not surprising that researchers, manufacturers and network providers are spending significant efforts to reduce the power consumption of ICT systems from dif- ferent angles. To this extent, networking devices waste a considerable amount of power. In partic- ular, their power consumption has always been increased in the last years, coupled with the increase of the offered performance [16]. Actually, power consumption of network- ing devices scales with the installed capacity, rather than the current load [17]. Thus, for an ISP the network power consumption is practically constant, unrespectively to traffic fluctuations. However, actual traffic is subject to strong day/night oscillations [3]. Thus, many devices are underutilized, especially during off-peak hours when traffic is low. This represents a clear opportunity for saving energy, since many resources (i.e., routers and links) are powered on without being fully utilized. In this context, resource consolidation is a known paradigm for the reduction of the power consumption. It consists in having a carefully selected subset of network devices entering a low power state, and use the rest to transport the required amountof traffic.

Recent years have witnessed a tremendous amount of research in the field of wireless sensor networks (WSNs) due to their numerous real-world applications in environmental and habitat monitoring, fire detection, object tracking, traffic controlling, industrial and machine-health control and monitoring, enemy-intrusion in military battlefields, and so on. However, reducing energy consumption of individual sensors in such networks and obtaining the expected standard of quality in the solutions provided by them is a major challenge. In this thesis, we investigate several problems in WSNs, particularly in the areas of broadcasting, routing, target monitoring, self-protecting networks, and topology control with an emphasis on minimizing and balancing energy consumption among the sensors in such networks. Several interesting theoretical results and bounds have been obtained for these problems which are further corroborated by extensive simulations of most of the algorithms. These empirical results lead us to believe that the algorithms may be applied in real-world situations where we can achieve a guarantee in the quality of solutions with a certain degree of balanced energy consumption among the sensors. / Thesis (Ph.D, Computing) -- Queen's University, 2010-04-27 10:19:39.03

volving technology, has kept drawing a significant attention from both the computing industry and academia for nearly a decade.

No description available.

No description available.

No / Continuously identifying a user’s location context provides new opportunities to understand daily life and human behavior. Indoor location systems have been mainly based on WiFi infrastructures which consume a great deal of energy mostly due to keeping the user’s WiFi device connected to the infrastructure and network communication, limiting the overall time when a user can be tracked. Particularly such tracking systems on battery-limited mobile devices must be energy-efficient to limit the impact on the experience of using a phone. Recently, there have been a lot of studies of energy-efficient positioning systems, but these have focused on outdoor positioning technologies. In this paper, we propose a novel indoor tracking framework that intelligently determines the location sampling rate and the frequency of network communication, to optimize the accuracy of the location data while being energy-efficient at the same time. This framework leverages an accelerometer, widely available on everyday smartphones, to reduce the duty cycle and the network communication frequency when a tracked user is moving slowly or not at all. Our framework can work for 14 h without charging, supporting applications that require this location information without affecting user experience.

Mobile ad hoc networks (MANETs) can be formed dynamically without the support of any existing infrastructure or any centralized administration. They consist of heterogeneous mobile nodes which are powered by batteries, move arbitrarily and are connected by wireless links. Battery energy limitation is one of the main challenges in the MANETs. Several hardware and software based techniques have been proposed in this field. Most of the previous studies have considered only the energy minimization of individual nodes and disregarded the overall network lifetime. Topology management is another important problem in MANETs, in this sense / several new computing paradigms have been developed by the researchers, and the topology management has not been studied clearly in most of these models. In this study, we propose two new techniques that deal with the topology management in order to facilitate the nodes&rsquo / cooperation towards energy saving. The developed computing model considers heterogeneous mobile nodes. A node that faces shortage in its resources (energy and processing capability) sends its work to one of the nearby devices which is able to execute the work. In addition, we propose two algorithm for dynamic and two for static task scheduling, to prolong the network life time. Comprehensive experiments showed that the proposed schemes achieve a significant improvement in the network lifetime while simultaneously reducing the energy consumption and time delay for each task.

Wireless Sensor Networks (WSNs) consist of Sensor Nodes (SNs) spatially removed from one another, that can monitor a variety of environmental conditions. SNs then collaboratively communicate the collected information to a central location, by passing along the data in a multi-hop fashion. SN energy resources are limited and energy monitoring and preservation in WSNs are therefore very important. Since multi-hop communication takes place, the routing protocol used may have a significant effect on the balanced use and preservation of energy in the WSN. A significant amount of research has been performed on energy efficient routing in WSNs, but the majority of these studies were only implemented in simulation. The simulation engines used to perform these studies do not take into account all of the relevant environmental factors affecting energy efficiency. In order to comment on the feasibility of a routing protocol meant to improve the energy efficiency of a WSN, it is important to test the routing scheme in a realistic environment. In this study, a SN specifically designed to be used in an energy consumption ascertaining WSN testbed was developed. This SN has a unique set of features which makes it ideal for this application. Each SN is capable of recording its own power consumption. The design also features a lithium battery charging circuit which improves the reusability of the SN. Each node has a detachable sensor module and transceiver module which enables the researcher to conduct experiments using various transceivers and sensors. Twenty of these SNs were then used to form an energy consumption ascertaining WSN testbed. This testbed was used to compare the energy consumption of a Minimum Total Transmission Power Routing (MTTPR) scheme to a shortest hop path routing scheme. The results show that each SN’s transmission power setting dependant efficiency has a significant effect on the overall performance of the MTTPR scheme. The MTTPR scheme might in some cases use more energy than a shortest hop path routing scheme because the transmission power setting dependant efficiency of the transceiver is not taken into account. The MTTPR scheme as well as other similar routing schemes can be improved by taking the transceiver efficiency at different transmission power settings into account. Simulation environments used to evaluate these routing schemes can also be improved by considering the transceiver efficiency at different transmission power settings. / MIng (Computer and Electronic Engineering), North-West University, Potchefstroom Campus, 2014

Wireless Sensor Networks (WSNs) consist of Sensor Nodes (SNs) spatially removed from one another, that can monitor a variety of environmental conditions. SNs then collaboratively communicate the collected information to a central location, by passing along the data in a multi-hop fashion. SN energy resources are limited and energy monitoring and preservation in WSNs are therefore very important. Since multi-hop communication takes place, the routing protocol used may have a significant effect on the balanced use and preservation of energy in the WSN. A significant amount of research has been performed on energy efficient routing in WSNs, but the majority of these studies were only implemented in simulation. The simulation engines used to perform these studies do not take into account all of the relevant environmental factors affecting energy efficiency. In order to comment on the feasibility of a routing protocol meant to improve the energy efficiency of a WSN, it is important to test the routing scheme in a realistic environment. In this study, a SN specifically designed to be used in an energy consumption ascertaining WSN testbed was developed. This SN has a unique set of features which makes it ideal for this application. Each SN is capable of recording its own power consumption. The design also features a lithium battery charging circuit which improves the reusability of the SN. Each node has a detachable sensor module and transceiver module which enables the researcher to conduct experiments using various transceivers and sensors. Twenty of these SNs were then used to form an energy consumption ascertaining WSN testbed. This testbed was used to compare the energy consumption of a Minimum Total Transmission Power Routing (MTTPR) scheme to a shortest hop path routing scheme. The results show that each SN’s transmission power setting dependant efficiency has a significant effect on the overall performance of the MTTPR scheme. The MTTPR scheme might in some cases use more energy than a shortest hop path routing scheme because the transmission power setting dependant efficiency of the transceiver is not taken into account. The MTTPR scheme as well as other similar routing schemes can be improved by taking the transceiver efficiency at different transmission power settings into account. Simulation environments used to evaluate these routing schemes can also be improved by considering the transceiver efficiency at different transmission power settings. / MIng (Computer and Electronic Engineering), North-West University, Potchefstroom Campus, 2014