Title

Classified power capping by network distribution trees for green computing

Authors

Authors

Z. K. Wu; C. Giles;J. Wang

Comments

Authors: contact us about adding a copy of your work at STARS@ucf.edu

Abbreviated Journal Title

Cluster Comput.

Keywords

Distribution tree; Power budgeting; Power consumption on the logical; level; SLA; Classified power capping; Cloud computing; Green computing; Computer Science, Information Systems; Computer Science, Theory &; Methods

Abstract

Power management is becoming very important in data centers. To apply power management in cloud computing, Green Computing has been proposed and considered. Cloud computing is one of the new promising techniques, that are appealing to many big companies. In fact, due to its dynamic structure and property in online services, cloud computing differs from current data centers in terms of power management. To better manage the power consumption of web services in cloud computing with dynamic user locations and behaviors, we propose a power budgeting design based on the logical level, using distribution trees. By setting multiple trees or forest, we can differentiate and analyze the effect of workload types and Service Level Agreements (SLAs, e.g. response time) in terms of power characteristics. Based on these, we introduce classified power capping for different services as the control reference to maximize power saving when there are mixed workloads.

Journal Title

Cluster Computing-the Journal of Networks Software Tools and Applications

Volume

16

Issue/Number

1

Publication Date

1-1-2013

Document Type

Article

Language

English

First Page

17

Last Page

26

WOS Identifier

WOS:000316011800003

ISSN

1386-7857

Share

COinS