Modelling energy efficiency in distributed home environments

Authors:
Helmut Hlavacs;Karin A. Hummel;Roman Weidlich;Amine M. Houyou;Hermann De Meer
Affiliations:
Department of Distributed and Multimedia Systems, University of Vienna, Lenaug. 2&#/#/47/8, 1080 Vienna, Austria.;Department of Distributed and Multimedia Systems, University of Vienna, Lenaug. 2&#/#/47/8, 1080 Vienna, Austria.;Department of Distributed and Multimedia Systems, University of Vienna, Lenaug. 2&#/#/47/8, 1080 Vienna, Austria.;Siemens AG, Corporate Technology, Otto-/Hahn-/Ring 6, Munich 81739, Germany/ Faculty of Computer Science and Mathematics, University of Passau, Innstr. 43, Passau 94032, Germany.;Faculty of Computer Science and Mathematics, University of Passau, Innstr. 43, Passau 94032, Germany
Venue:
International Journal of Communication Networks and Distributed Systems
Year:
2010

Citing 6
Cited 2

A Survey of Energy Efficient Network Protocols for Wireless Networks

Wireless Networks
Queueing Networks and Markov Chains

Queueing Networks and Markov Chains
The design principles of PlanetLab

ACM SIGOPS Operating Systems Review
Client-Centered, Energy-Efficient Wireless Communication on IEEE 802.11b Networks

IEEE Transactions on Mobile Computing
JouleSort: a balanced energy-efficiency benchmark

Proceedings of the 2007 ACM SIGMOD international conference on Management of data
Estimating churn in structured P2P networks

ITC20'07 Proceedings of the 20th international teletraffic conference on Managing traffic performance in converged networks

Approximation towards energy-efficient distributed environments

Proceedings of the 3rd International ICST Conference on Simulation Tools and Techniques
Using existing network infrastructure to estimate building occupancy and control plugged-in devices in user workspaces

International Journal of Communication Networks and Distributed Systems

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper, we present a distributed approach for saving energy by sharing computing load in home networks. In our approach, possibly thousands of home computers may cooperate and send each other tasks which include services and applications running on a 24/7 basis. By concentrating as many tasks as possible on a small number of computers, idle computers may go asleep and thus consume almost no energy. We present the general architecture of our approach and analyse several 24/7 applications by modelling the potential energy consumption with and without application sharing, as well as the aspect of availability.