By Topic

An Energy Aware Network Management Approach Using Server Profiling in 'Green' Clouds

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

7 Author(s)
Peoples, C. ; Sch. of Comput. & Inf. Eng., Univ. of Ulster Coleraine, Coleraine, UK ; Parr, G. ; McClean, S. ; Scotney, B.
more authors

Clouds and data centres are significant consumers of power. There are however, opportunities for optimising carbon cost here as resource redundancy is provisioned extensively. Data centre resources, and subsequently clouds which support them, are traditionally organised into tiers; switch-off activity when managing redundant resources therefore occurs in an approach which exploits cost advantages associated with closing down entire network portions. We suggest however, an alternative approach to optimise cloud operation while maintaining application QoS: Simulation experiments identify that network operation can be optimised by selecting servers which process traffic at a rate that more closely matches the packet arrival rate, and resources which provision excessive capacity additional to that required may be powered off for improved efficiency. This recognises that there is a point in server speed at which performance is optimised, and operation which is greater than or less than this rate will not achieve optimisation. A series of policies have been defined in this work for integration into cloud management procedures; performance results from their implementation and evaluation in simulation show improved efficiency by selecting servers based on these relationships.

Published in:

Network Cloud Computing and Applications (NCCA), 2012 Second Symposium on

Date of Conference:

3-4 Dec. 2012