Advanced Search

Journal Navigation

Journal Home

Subscriptions

Archive

Contact Us

Table of Contents

Click here to sign up for SAGE Journal Email Alerts today!

Sign In to gain access to subscriptions and/or personal tools.
International Journal of High Performance Computing Applications
This Article
Right arrow Full Text (PDF)
Right arrow References
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in Web of Science
Right arrow Alert me to new issues of the journal
Right arrow Add to Saved Citations
Right arrow Download to citation manager
Right arrowRequest Permissions
Right arrow Request Reprints
Right arrow Add to My Marked Citations
Citing Articles
Right arrow Citing Articles via Google Scholar
Right arrow Citing Articles via Scopus
Google Scholar
Right arrow Articles by Gurun, S.
Right arrow Articles by Nurmi, D.
Right arrow Search for Related Content
Social Bookmarking
Add to CiteULike   Add to Complore   Add to Connotea   Add to Del.icio.us   Add to Digg   Add to Reddit   Add to Technorati   Add to Twitter  
What's this?

On the Efficacy of Computation Offloading Decision-Making Strategies

Selim Gurun

COMPUTER SCIENCE DEPARTMENT, UNIVERSITY OF CALIFORNIA, SANTA BARBARA, GURUN{at}CS.UCSB.EDU

Rich Wolski

COMPUTER SCIENCE DEPARTMENT, UNIVERSITY OF CALIFORNIA, SANTA BARBARA

Chandra Krintz

COMPUTER SCIENCE DEPARTMENT, UNIVERSITY OF CALIFORNIA, SANTA BARBARA

Dan Nurmi

COMPUTER SCIENCE DEPARTMENT, UNIVERSITY OF CALIFORNIA, SANTA BARBARA

We present a framework for making computation offloading decisions in computational grid settings in which schedulers determine when to move parts of a computation to more capable resources to improve performance. Such schedulers must predict when an offloaded computation will outperform one that is local by forecasting the local cost (execution time for computing locally) and remote cost (execution time for computing remotely and transmission time for the input/output of the computation to/from the remote system). Typically, this decision amounts to predicting the bandwidth between the local and remote systems to estimate these costs. Our framework unifies such decision models by formulating the problem as a statistical decision problem that can either be treated "classically" or using a Bayesian approach. Using an implementation of this framework, we evaluate the efficacy of a number of different decision strategies (several of which have been employed by previous systems). Our results indicate that a Bayesian approach employing automatic change-point detection when estimating the prior distribution is the best performing approach.

Key Words: computational grid • computation offloading • remote execution • network prediction • RPC

International Journal of High Performance Computing Applications, Vol. 22, No. 4, 460-479 (2008)
DOI: 10.1177/1094342007095289
Add to CiteULike CiteULike   Add to Complore Complore   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us   Add to Digg Digg   Add to Reddit Reddit   Add to Technorati Technorati   Add to Twitter Twitter    What's this?