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Optimizing Server Power Consumption in Cross-Domain Content Distribution Infrastructures

Ge, Chang, Wang, Ning and Sun, Zhili (2012) Optimizing Server Power Consumption in Cross-Domain Content Distribution Infrastructures In: IEEE International Conference on Communications (ICC) 2012, 12 - 15 June 2012, Ottawa, Canada.

ChangGe-ICC2012.pdf - Accepted version Manuscript

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Optimizing server’s power consumption in content distribution infrastructure has attracted increasing research efforts. The technical challenge is the tradeoff between server power consumption and the content service capability on both the server and the network side. This paper proposes and evaluates a novel approach that optimizes content servers’ power consumptions in large-scale content distribution platforms across multiple ISP domains. Specifically, our approach strategically puts servers to sleep mode without violating load capacities of virtual content delivery links and active servers in the infrastructure. Such a problem can be formulated into a nonlinear programming model. The efficiency of our approach is evaluated in a content distribution topology covering two real interconnected domains. The simulation has shown that our approach is capable of reducing servers’ power consumptions by up to 62.2%, while maintaining the actual service performance in an acceptable scope.

Item Type: Conference or Workshop Item (Conference Paper)
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering > Centre for Communication Systems Research
Authors :
Date : November 2012
DOI : 10.1109/ICC.2012.6363659
Copyright Disclaimer : © 2012 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Depositing User : Ning Wang
Date Deposited : 02 Jan 2013 10:21
Last Modified : 16 Jan 2019 16:40

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