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Joint virtual machine assignment and traffic engineering for green data center networks

Joint virtual machine assignment and traffic engineering for green data center networks Joint Virtual Machine Assignment and Traffic Engineering for Green Data Center Networks Lin Wang , Fa Zhang , Athanasios V. Vasilakos , Chenying Hou , Zhiyong Liu Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China University of Western Macedonia, Athens, Greece University of Chinese Academy of Sciences, Beijing, China State Key Labotary for Computer Architecture, ICT, CAS, Beijing, China {wanglin, zhangfa, houchenying, zyliu}@ict.ac.cn, vasilako@ath.forthnet.gr center, the first attention would be paid on the servers, since all tasks have to be processed by servers. However, when sophisticated energy-efficient techniques are involved in servers, the energy consumed by the huge amount of network devices (mainly switches) used for providing sufficient connection bandwidth between each pair of servers also emerges as a first-order concern. It has been pointed out by Abts et al. [1] that in a typical data center from Google the power consumed by the network takes a fraction of 20% of the total consumption when the servers are fully utilized, but this fraction will increase to 50% if the server utilization decreases to 15% which is a normal case in reality. Therefore, it is also eager to have efficient strategies for greening the network in data http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png ACM SIGMETRICS Performance Evaluation Review Association for Computing Machinery

Joint virtual machine assignment and traffic engineering for green data center networks

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Publisher
Association for Computing Machinery
Copyright
Copyright © 2014 by ACM Inc.
ISSN
0163-5999
DOI
10.1145/2567529.2567560
Publisher site
See Article on Publisher Site

Abstract

Joint Virtual Machine Assignment and Traffic Engineering for Green Data Center Networks Lin Wang , Fa Zhang , Athanasios V. Vasilakos , Chenying Hou , Zhiyong Liu Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China University of Western Macedonia, Athens, Greece University of Chinese Academy of Sciences, Beijing, China State Key Labotary for Computer Architecture, ICT, CAS, Beijing, China {wanglin, zhangfa, houchenying, zyliu}@ict.ac.cn, vasilako@ath.forthnet.gr center, the first attention would be paid on the servers, since all tasks have to be processed by servers. However, when sophisticated energy-efficient techniques are involved in servers, the energy consumed by the huge amount of network devices (mainly switches) used for providing sufficient connection bandwidth between each pair of servers also emerges as a first-order concern. It has been pointed out by Abts et al. [1] that in a typical data center from Google the power consumed by the network takes a fraction of 20% of the total consumption when the servers are fully utilized, but this fraction will increase to 50% if the server utilization decreases to 15% which is a normal case in reality. Therefore, it is also eager to have efficient strategies for greening the network in data

Journal

ACM SIGMETRICS Performance Evaluation ReviewAssociation for Computing Machinery

Published: Jan 10, 2014

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