Resource design in constrained networks for network lifetime increase

As constrained "things" become increasingly integrated with the Internet and accessible for interactive communication, energy efficient ways to collect, aggregate, and share data over such constrained networks are needed. In this paper, we propose the use of constrained RESTful environments interfaces to build resource collections having a network lifetime increase in mind. More specifically, based on existing atomic resources, collections are created/designed to become available as new resources, which can be observed. Such resource design should not only match client's interests, but also increase network lifetime as much as possible. For this to happen, energy consumption should be balanced/fair among nodes so that node depletion is delayed. When compared with previous approaches, results show that energy efficiency and network lifetime can be increased while reducing control/registration messages, which are used to set up or change observations

Storage Space Optimisation for Green Data Center

The characteristic that determines a green data center is low amount of carbon footprint produced by its physical data storages. Increasing demand of data volumes in many data intensive applications call for additional physical data storages that are not only impractically large to maintain, but also contribute to the amount of carbon footprint produced. It is argued in this paper that, if storage space can be optimised to gain free spaces, the storage space requirement can be reduced. In this paper, a model to optimize database storage space by mining functional dependencies that are present among data sets is proposed. Sample data sets from the microbial domain have been used where data of large data volume raises storage space concern. The initial results of the implementation of the model that is necessary in designing a complete space optimization algorithm are presented

System for improving the efficiency of wireless networks

Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2003.Includes bibliographical references (p. 30-31).Wireless data networks are widespread and growing quickly. As their use increases, many wireless networks are becoming congested. In addition, as wireless data capability moves into ever-smaller devices, power becomes a significant issue. This thesis presents a system that increases network bandwidth and decreases energy use without changing existing network hardware or protocols. We use specialized proxy servers to transparently modify the traffic sent over the mobile link such that the total energy used by the receiver is reduced and the effective bandwidth is increased. Our techniques include optimizing packet size, eliminating unnecessary traffic, and masking wireless packet losses. We design and implement two proxies--one for access points and one for mobile devices--which when used together, achieve up to a 20% decrease in energy and 38% increase in throughput.by Hans Robertson.M.Eng

Reducing Electricity Demand Charge for Data Centers with Partial Execution

Data centers consume a large amount of energy and incur substantial electricity cost. In this paper, we study the familiar problem of reducing data center energy cost with two new perspectives. First, we find, through an empirical study of contracts from electric utilities powering Google data centers, that demand charge per kW for the maximum power used is a major component of the total cost. Second, many services such as Web search tolerate partial execution of the requests because the response quality is a concave function of processing time. Data from Microsoft Bing search engine confirms this observation. We propose a simple idea of using partial execution to reduce the peak power demand and energy cost of data centers. We systematically study the problem of scheduling partial execution with stringent SLAs on response quality. For a single data center, we derive an optimal algorithm to solve the workload scheduling problem. In the case of multiple geo-distributed data centers, the demand of each data center is controlled by the request routing algorithm, which makes the problem much more involved. We decouple the two aspects, and develop a distributed optimization algorithm to solve the large-scale request routing problem. Trace-driven simulations show that partial execution reduces cost by $3\%--10.5\%$ for one data center, and by $15.5\%$ for geo-distributed data centers together with request routing.Comment: 12 page

Greening information management: final report

As the recent JISC report on ‘the ‘greening’ of ICT in education [1] highlights, the increasing reliance on ICT to underpin the business functions of higher education institutions has a heavy environmental impact, due mainly to the consumption of electricity to run computers and to cool data centres. While work is already under way to investigate how more energy efficient ICT can be introduced, to date there has been much less focus on the potential environmental benefits to be accrued from reducing the demand ‘at source’ through better data and information management. JISC thus commissioned the University of Strathclyde to undertake a study to gather evidence that establishes the efficacy of using information management options as components of Green ICT strategies within UK Higher Education environments, and to highlight existing practices which have the potential for wider replication

A Survey of Green Networking Research

Reduction of unnecessary energy consumption is becoming a major concern in wired networking, because of the potential economical benefits and of its expected environmental impact. These issues, usually referred to as "green networking", relate to embedding energy-awareness in the design, in the devices and in the protocols of networks. In this work, we first formulate a more precise definition of the "green" attribute. We furthermore identify a few paradigms that are the key enablers of energy-aware networking research. We then overview the current state of the art and provide a taxonomy of the relevant work, with a special focus on wired networking. At a high level, we identify four branches of green networking research that stem from different observations on the root causes of energy waste, namely (i) Adaptive Link Rate, (ii) Interface proxying, (iii) Energy-aware infrastructures and (iv) Energy-aware applications. In this work, we do not only explore specific proposals pertaining to each of the above branches, but also offer a perspective for research.Comment: Index Terms: Green Networking; Wired Networks; Adaptive Link Rate; Interface Proxying; Energy-aware Infrastructures; Energy-aware Applications. 18 pages, 6 figures, 2 table

Topics in Power Usage in Network Services

The rapid advance of computing technology has created a world powered by millions of computers. Often these computers are idly consuming energy unnecessarily in spite of all the efforts of hardware manufacturers. This thesis examines proposals to determine when to power down computers without negatively impacting on the service they are used to deliver, compares and contrasts the efficiency of virtualisation with containerisation, and investigates the energy efficiency of the popular cryptocurrency Bitcoin. We begin by examining the current corpus of literature and defining the key terms we need to proceed. Then we propose a technique for improving the energy consumption of servers by moving them into a sleep state and employing a low powered device to act as a proxy in its place. After this we move on to investigate the energy efficiency of virtualisation and compare the energy efficiency of two of the most common means used to do this. Moving on from this we look at the cryptocurrency Bitcoin. We consider the energy consumption of bitcoin mining and if this compared with the value of bitcoin makes this profitable. Finally we conclude by summarising the results and findings of this thesis. This work increases our understanding of some of the challenges of energy efficient computation as well as proposing novel mechanisms to save energy

Coordinated en-route transcoding caching for tree networks

©2004 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.As transcoding caching is attracting an increasing amount of attention, it is important and necessary to find methods to distribute multiple versions of the same media object in the Internet. In this paper, we first present a mathematical model for the problem of optimally determining the locations in which to place multiple versions of the same media object in tree networks such that the specified objective is achieved. This problem is formulated as an optimization problem. Second, we propose a low-cost dynamic programming-based solution for solving this problem, by which the optimal locations are obtained. Finally, we evaluate our model on different performance metrics through extensive simulation experiments and compare the results of our model with those of existing models that consider transcoding caching either on a path or at individual nodes only.Keqiu Li, Hong She

Transcoding proxy placement in en-route web caching

Copyright © 2004 IEEEWith the rapid growth of audio and video applications on the internet, caching media objects in transcoding proxies has become an important research topic in recent years. In this paper, we address the problem of finding the optimal locations for placing fixed number of transcoding proxies among the nodes in a network such that the specified objective is achieved. We present an original model for this problem, which makes transcoding proxy placement decisions on all the en-route nodes along the routing path in a coordinated way. In our model, proxy status information along the routing path of requests is used for optimally determining the locations for placing fixed number of transcoding proxies. We formulate this problem as an optimization problem and the optimal locations are obtained using a low-cost dynamic programming-based algorithm. We implement our algorithm and evaluate our model on different performance metrics through extensive simulation experiments. The implementation results show that our model significantly outperforms the random algorithm which places transcoding proxies among the nodes in a network randomly.Keqiu Li, Hong She