By Topic

Dynamic computing resource adjustment for enhancing energy efficiency of cloud service data centers

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

2 Author(s)
Cheng-Jen Tang ; Dept. of Electr. Eng., Tatung Univ., Taipei, Taiwan ; Miau-Ru Dai

Cloud computing clusters distributed computers to provide applications as services and on-demand resources over Internet. From the perspective of average and total energy consumption, such consolidated resource enhances the energy efficiency on both clients and servers. However, cloud computing has a different power consumption pattern from the traditional storage oriented Internet services. The computation oriented implementation of cloud service broadens the gap between the peak power demand and base power demand of a data center. A higher peak demand implies the need of feeder capacity expansion, which requires a considerable investment. This study proposes a computation related approach to lessen the increasing power demand of cloud service data centers. Through appropriated designs, some frequently used computing algorithms can be performed by either clients or servers. As a model presented in this paper, such client-server balanced computation resource integration suggests an energy-efficient and cost-effective cloud service data center.

Published in:

System Integration (SII), 2011 IEEE/SICE International Symposium on

Date of Conference:

20-22 Dec. 2011