Enhanced heuristics to reduce power consumption of networks using weight setting

Aldraho, Abdelnour and Kist, Alexander A. (2010) Enhanced heuristics to reduce power consumption of networks using weight setting. In: 2010 Southern Region Engineering Conference (SREC 2010), 11-12 Nov 2010, Toowoomba, Australia.

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Abstract

Energy consumption of communication networks is an important contributor to the ICT sector's greenhouse gas emission footprint. This research project focuses on power consumption reduction of communication networks by dynamically adapting network configuration to traffic demands. This is promising as networks are often under utilised over long periods. In the context of this work, dynamic topologies refers to a method of changing network links and nodes according to traffic loads. In this paper preliminary results are introduced and two simple heuristics are investigated: the Lightest Node First and the Least Loaded Node algorithms. Both generate reduced topologies for given traffic loads with smaller energy footprints than unmodified networks. Initial numerical results are presented for a small sample network of eight nodes 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 50% for this sample network.

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Item Type:	Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)
Refereed:	Yes
Item Status:	Live Archive
Additional Information:	USQ conference. Proceedings available in http://www.usq.edu.au/engsummit/proceedings
Faculty/School / Institute/Centre:	Historic - Faculty of Engineering and Surveying - Department of Electrical, Electronic and Computer Engineering (Up to 30 Jun 2013)
Faculty/School / Institute/Centre:	Historic - Faculty of Engineering and Surveying - Department of Electrical, Electronic and Computer Engineering (Up to 30 Jun 2013)
Date Deposited:	14 Feb 2011 05:26
Last Modified:	03 Jul 2013 00:28
Uncontrolled Keywords:	dynamic topology; weight setting; power consumption
Fields of Research (2008):	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)
Socio-Economic Objectives (2008):	E Expanding Knowledge > 97 Expanding Knowledge > 970109 Expanding Knowledge in Engineering
URI:	http://eprints.usq.edu.au/id/eprint/18277

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