Joint Bandwidth Assignment and Routing for Power Saving on Large File Transfer with Time Constraints

The increase in network traffic in recent years has led to increased power consumption. Accordingly, many studies have tried to reduce the energy consumption of network devices. Various types of data have become available in large quantities via large high-speed computer networks. Time-constrained file transfer is receiving much attention as an advanced service. In this model, a request must be completed within a user-specified deadline or rejected if the requested deadline cannot be met. Some bandwidth assignment and routing methods to accept more requests have been proposed. However, these existing methods do not consider energy consumption. Herein, we propose a joint bandwidth assignment and routing method that reduces energy consumption for time-constrained large file transfer. The bandwidth assignment method reduces the power consumption of mediate node, typically router, by waiting for requests and transferring several requests at the same time. The routing method reduces the power consumption by selecting the path with the least predicted energy consumption. Finally, we evaluate the proposed method through simulation experiments

Energy Efficient Nano Servers Provisioning for Information Piece Delivery in a Vehicular Environment

In this paper, we propose energy efficient Information Piece Delivery (IPD) through Nano Servers (NSs) in a vehicular network. Information pieces may contain any data that needs to be communicated to a vehicle. The available power (renewable or non-renewable) for a NS is variable. As a result, the service rate of a NS varies linearly with the available energy within a given range. Our proposed system therefore exhibits energy aware rate adaptation (RA), which uses variable transmission energy. We have also developed another transmission energy saving method for comparison, where sleep cycles (SC) are employed. Both methods are compared against an acceptable download time. To reduce the operational energy, we first optimise the locations of the NSs by developing a mixed integer linear programming (MILP) model, which takes into account the hourly variation of the traffic. The model is validated through a Genetic Algorithm (GA1). Furthermore, to reduce the gross delay over the entire vehicular network, the available renewable energy (wind farm) is optimally allocated to each NS according to piece demand. This, in turn, also reduces the network carbon footprint. A Genetic Algorithm (GA2) is also developed to validate the MILP results associated with this system. Through transmission energy savings, RA and SC further reduce the NSs energy consumption by 19% and 18% respectively, however at the expense of higher download time. MILP model 4 (with RA) and model 5 (with SC) reduced the delay by 81% and 83% respectively, while minimising the carbon footprint by 96% and 98% respectively, compared to the initial MILP model

A quantitative survey of the power saving potential in IP-Over-WDM backbone networks

The power consumption in Information and Communication Technologies networks is growing year by year; this growth presents challenges from technical, economic, and environmental points of view. This has lead to a great number of research publications on "green" telecommunication networks. In response, a number of survey works have appeared as well. However, with respect to backbone networks, most survey works: 1) do not allow for an easy cross validation of the savings reported in the various works and 2) nor do they provide a clear overview of the individual and combined power saving potentials. Therefore, in this paper, we survey the reported saving potential in IP-over-WDM backbone telecommunication networks across the existing body of research in that area. We do this by mapping more than ten different approaches to a concise analytical model, which allows us to estimate the combined power reduction potential. Our estimates indicate that the power reduction potential of the once-only approaches is 2.3x in a Moderate Effort scenario and 31x in a Best Effort scenario. Factoring in the historic and projected yearly efficiency improvements ("Moore's law") roughly doubles both values on a ten-year horizon. The large difference between the outcome of Moderate Effort and Best Effort scenarios is explained by the disparity and lack of clarity of the reported saving results and by our (partly) subjective assessment of the feasibility of the proposed approaches. The Moderate Effort scenario will not be sufficient to counter the projected traffic growth, although the Best Effort scenario indicates that sufficient potential is likely available. The largest isolated power reduction potential is available in improving the power associated with cooling and power provisioning and applying sleep modes to overdimensioned equipment

Green Computing - Desktop Computer Power Management at the City of Tulsa

One type of Green Computing focuses on reducing power consumption of computers. Specialized software like 1E/Nightwatchman aids in reducing the power consumption of desktop computers by placing them in a low power state when not in use. This thesis describes the implementation of 1E/Nightwatchman power management software on two thousand desktop computers at the City of Tulsa. It shows the method used to predict power savings of 100,000.00 per year and compares the prediction to the actual savings after one year of operation.Computer Scienc

Energy Efficient Content Distribution

To optimize energy efficiency in network, operators try to switch off as many network devices as possible. Recently, there is a trend to introduce content caches as an inherent capacity of network equipment, with the objective of improving the efficiency of content distribution and reducing network congestion. In this work, we study the impact of using in-network caches and CDN cooperation on an energy-efficient routing. We formulate this problem as Energy Efficient Content Distribution. The objective is to find a feasible routing, so that the total energy con- sumption of the network is minimized subject to satisfying all the demands and link capacity. We exhibit the range of parameters (size of caches, popularity of content, demand intensity, etc.) for which caches are useful. Experiment results show that by placing a cache on each backbone router to store the most popular content, along with well choosing the best content provider server for each demand to a CDN, we can save a total up to 23% of power in the backbone, while 16% can be gained solely thanks to caches.Pour optimiser l'efficacité énergétique dans un réseau, les opérateurs doivent éteindre un nombre maximum d'équipements réseau. Récemment, il a été propose de rajouter des caches à l'intérieur des nœuds réseaux dans l'objectif d'améliorer la distribution de contenus et de réduire la congestion des réseaux. Dans ce travail, nous étudions l'impact de l'utilisation de caches réseaux (in- network caches) et de leur coopération avec les Content Delivery Networks (CDN) sur l'énergie consommée par le routage. Nous modélisons ce problème, la Distribution de Données Efficace en Énergie. L'objectif est de trouver un routage réalisable qui minimise la consommation énergétique du réseau tout en satisfaisant les demandes de contenus. Nous exhibons les valeurs des paramètres (tailles des caches, popularités des données, ...) pour lesquelles ces caches sont utiles. Des expérimentations montrent qu'en plaçant un cache sur chaque routeur d'un réseau backbone pour stocker le contenu le plus populaire, ainsi qu'on choisissant le meilleur serveur pour chaque demande 'a un CDN, jusqu'à 23% de l'énergie du backbone peut être sauvée, dont 16% du gain est du aux seuls caches

On the Energy Efficiency of Networked Systems

Energy is a first-class resource for datacenter operators since its cost is the biggest limiting factor in scaling a large computing facility. The solution embraced by major operators is to build their facilities in strategic geographical locations and to abandon expensive specialized hardware for cheap commodity systems. However, such systems are not efficient when it comes to energy and a considerable amount of research effort has been put in finding a solution to this problem. Furthermore, the need for more programmable and flexible networking devices is pushing the need for hardware commoditization also within the datacenter network. In this thesis we propose two solutions aimed at improving the overall energy efficiency of a datacenter facility. The first address efficiency in computing, by proposing a different hardware architecture for server systems. We propose a hybrid architecture that blends traditional server processors with very-low-power processors from the mobile devices world. The second solution envisions the usage of current server platforms as network switches or routers and provides guidelines for the implementation of power saving algorithms that do not affect peak performance while saving up to 50% power. This work is based on both theoretical modeling and simulation and experimentation with real-world prototypes

DESIGN OF RELIABLE AND SUSTAINABLE WIRELESS SENSOR NETWORKS: CHALLENGES, PROTOCOLS AND CASE STUDIES

Integrated with the function of sensing, processing, and wireless communication, wireless sensors are attracting strong interest for a variety of monitoring and control applications. Wireless sensor networks (WSNs) have been deployed for industrial and remote monitoring purposes. As energy shortage is a worldwide problem, more attention has been placed on incorporating energy harvesting devices in WSNs. The main objective of this research is to systematically study the design principles and technical approaches to address three key challenges in designing reliable and sustainable WSNs; namely, communication reliability, operation with extremely low and dynamic power sources, and multi-tier network architecture. Mathematical throughput models, sustainable WSN communication strategies, and multi-tier network architecture are studied in this research to address these challenges, leading to protocols for reliable communication, energy-efficient operation, and network planning for specific application requirements. To account for realistic operating conditions, the study has implemented three distinct WSN testbeds: a WSN attached to the high-speed rotating spindle of a turning lathe, a WSN powered by a microbial fuel cell based energy harvesting system, and a WSN with a multi-tier network architecture. With each testbed, models and protocols are extracted, verified and analyzed. Extensive research has studied low power WSNs and energy harvesting capabilities. Despite these efforts, some important questions have not been well understood. This dissertation addresses the following three dimensions of the challenge. First, for reliable communication protocol design, mathematical throughput or energy efficiency estimation models are essential, yet have not been investigated accounting for specific application environment characteristics and requirements. Second, for WSNs with energy harvesting power sources, most current networking protocols do not work efficiently with the systems considered in this dissertation, such as those powered by extremely low and dynamic energy sources. Third, for multi-tier wireless network system design, routing protocols that are adaptive to real-world network conditions have not been studied. This dissertation focuses on these questions and explores experimentally derived mathematical models for designing protocols to meet specific application requirements. The main contributions of this research are 1) for industrial wireless sensor systems with fast-changing but repetitive mobile conditions, understand the performance and optimal choice of reliable wireless sensor data transmission methods, 2) for ultra-low energy harvesting wireless sensor devices, design an energy neutral communication protocol, and 3) for distributed rural wireless sensor systems, understand the efficiency of realistic routing in a multi-tier wireless network. Altogether, knowledge derived from study of the systems, models, and protocols in this work fuels the establishment of a useful framework for designing future WSNs