DocumentCode
3400292
Title
Incorporating Rate Adaptation Into Green Networking for Future Data Centers
Author
Lin Wang ; Fa Zhang ; Chenying Hou ; Arjona Aroca, Jordi ; Zhiyong Liu
Author_Institution
Inst. of Comput. Technol., Beijing, China
fYear
2013
fDate
22-24 Aug. 2013
Firstpage
106
Lastpage
109
Abstract
Despite some proposals for energy-efficient topologies, most of the studies for saving energy in data center networks are focused on traffic engineering, i.e., consolidating flows and switching off unnecessary network devices. The major weakness of this approach is network oscillation brought by the frequent change of network topology when traffic fluctuates very fast. In this paper, we propose to incorporate rate adaptation into green data center networks. With rate adaptive network devices, we aim at approaching network-wide energy proportionality by routing optimization. We formalize the problem with an integer program and propose an efficient approximation algorithm - TSRR, solving the problem quickly while guaranteeing a constant performance ratio. Extensive range of simulations confirm that more than 40% of the energy can be saved while introducing very slight stretch on network delay.
Keywords
computer centres; energy conservation; green computing; integer programming; network servers; telecommunication network routing; telecommunication network topology; telecommunication traffic; TSRR algorithm; approximation algorithm; constant performance ratio; energy saving; energy-efficient topologies; future data centers; green data center networks; integer program; network delay; network oscillation; network topology; network-wide energy proportionality; rate adaptive network devices; routing optimization; traffic engineering; Adaptation models; Approximation algorithms; Approximation methods; Green products; Network topology; Optimization; Routing;
fLanguage
English
Publisher
ieee
Conference_Titel
Network Computing and Applications (NCA), 2013 12th IEEE International Symposium on
Conference_Location
Cambridge, MA
Print_ISBN
978-0-7695-5043-5
Type
conf
DOI
10.1109/NCA.2013.24
Filename
6623649
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