Heuristics for dynamic topologies to reduce power consumption of networks

Aldraho, Abdelnour and Kist, Alexander A. (2010) Heuristics for dynamic topologies to reduce power consumption of networks. In: ATNAC 2010: Australasian Telecommunication Networks and Applications Conference, 31 Oct-3 Nov 2010, Auckland, New Zealand.

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Abstract

Energy consumption of communication networks is an important contributor to the ICT sector's greenhouse gas emission footprint. Networks are generally dimensioned for peak loads. Over long periods, networks are under utilised, and at the same time their energy consumption remains high. This research focuses on the reduction of power consumption of communication networks by adapting network topology to traffic demands. Dynamic topologies refer to a method of changing network links and notes according to traffic loads. This paper investigates two heuristics: the Lightest Node First and the Least Loaded Node algorithms that find topologies for given traffic loads, that have a smaller energy footprint, but are able to accommodate traffic loads. Numerical results are presented for a sample network with a large set of traffic demands. Depending on overall network utilisation, the algorithms are able to reduce the average network power consumption by up to 40%.


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Item Type: Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)
Refereed: Yes
Item Status: Live Archive
Additional Information: Accepted version deposited in accordance with the copyright policy of the publisher.
Depositing User: Dr Alexander Kist
Faculty / Department / School: Historic - Faculty of Engineering and Surveying - Department of Electrical, Electronic and Computer Engineering
Date Deposited: 14 Feb 2011 06:00
Last Modified: 02 Sep 2014 21:59
Uncontrolled Keywords: energy efficiency; network optimisation; context; Heuristic algorithms; network topology; optimization; power demand; routing; topology
Fields of Research (FOR2008): 10 Technology > 1005 Communications Technologies > 100503 Computer Communications Networks
09 Engineering > 0906 Electrical and Electronic Engineering > 090607 Power and Energy Systems Engineering (excl. Renewable Power)
10 Technology > 1005 Communications Technologies > 100599 Communications Technologies not elsewhere classified
Socio-Economic Objective (SEO2008): E Expanding Knowledge > 97 Expanding Knowledge > 970109 Expanding Knowledge in Engineering
Identification Number or DOI: doi: 10.1109/ATNAC.2010.5680252
URI: http://eprints.usq.edu.au/id/eprint/18315

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