Heuristics for dynamic topologies to reduce power consumption of networks
Paper
Paper/Presentation Title | Heuristics for dynamic topologies to reduce power consumption of networks |
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Presentation Type | Paper |
Authors | Aldraho, Abdelnour (Author) and Kist, Alexander A. (Author) |
Editors | Al-Anbuky, Adnan |
Journal or Proceedings Title | Proceedings of the Australasian Telecommunication Networks and Applications Conference (ATNAC 2010) |
ERA Conference ID | 50278 |
Number of Pages | 6 |
Year | 2010 |
Place of Publication | United States |
ISBN | 9781424481736 |
9781424481712 | |
Digital Object Identifier (DOI) | https://doi.org/10.1109/ATNAC.2010.5680252 |
Web Address (URL) of Paper | https://ieeexplore.ieee.org/document/5680252 |
Web Address (URL) of Conference Proceedings | https://ieeexplore.ieee.org/xpl/conhome/5673793/proceeding |
Conference/Event | Australasian Telecommunication Networks and Applications Conference (ATNAC 2010) |
Australasian Telecommunication Networks and Applications Conference | |
Event Details | Australasian Telecommunication Networks and Applications Conference (ATNAC 2010) Event Date 31 Oct 2010 to end of 03 Nov 2010 Event Location Auckland, New Zealand |
Event Details | Australasian Telecommunication Networks and Applications Conference ATNAC |
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%. |
Keywords | energy efficiency; network optimisation; context; Heuristic algorithms; network topology; optimization; power demand; routing; topology |
ANZSRC Field of Research 2020 | 400604. Network engineering |
400805. Electrical energy transmission, networks and systems | |
409999. Other engineering not elsewhere classified | |
Public Notes | Files associated with this item cannot be displayed due to copyright restrictions. |
Byline Affiliations | Faculty of Engineering and Surveying |
Department of Electrical, Electronic and Computer Engineering | |
Institution of Origin | University of Southern Queensland |
https://research.usq.edu.au/item/q079w/heuristics-for-dynamic-topologies-to-reduce-power-consumption-of-networks
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