Multi-level power and performance tradeoffs across the access networks to customer premises equipment

Jain, V., Parr, G.P. ORCID: https://orcid.org/0000-0002-9365-9132, Morrow, P.J. and Polaine, M. (2011) Multi-level power and performance tradeoffs across the access networks to customer premises equipment. In: 2011 International Green Computing Conference and Workshops, IGCC 2011. The Institute of Electrical and Electronics Engineers (IEEE), USA. ISBN 978-1-4577-1222-7

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Abstract

Across broadband access networks, significant opportunities to minimise energy consumption exist at the application and networks level but are not fully coordinated. For example, an application can tune its QoS in accordance with the available power levels of network systems. As a first step towards enabling energy efficiency, we study the inter-relationship between energy consumption and application performance in a residential home-gateway. The study reveals the power and application performance trade-offs in broadband access networks and then employs an agent based approach that works together in accordance with a flexible set of power-performance objectives and determines the existence of a feasible coordinated operating point. The key elements of our approach include (a) a power-performance polygon-based methodology which automatically selects power management settings that keep the pathway from access network to home-gateway operating close to the optimal operating point (b) a multi-agent policy-based approach which adaptively manages performance and power consumption based on varying traffic load during peak/off-peak hours. Finally, the efficiency of the model is demonstrated by the initial results of the experiments.

Item Type:	Book Section
Faculty \ School:	Faculty of Science > School of Computing Sciences
UEA Research Groups:	Faculty of Science > Research Groups > Smart Emerging Technologies Faculty of Science > Research Groups > Cyber Security Privacy and Trust Laboratory Faculty of Science > Research Groups > Data Science and AI
Depositing User:	Pure Connector
Date Deposited:	24 Sep 2016 01:07
Last Modified:	10 Dec 2024 01:10
URI:	https://ueaeprints.uea.ac.uk/id/eprint/60514
DOI:	10.1109/IGCC.2011.6008587

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