Scheduled System Maintenance:
On Wednesday, July 29th, IEEE Xplore will undergo scheduled maintenance from 7:00-9:00 AM ET (11:00-13:00 UTC). During this time there may be intermittent impact on performance. We apologize for any inconvenience.
By Topic

Parallel Loop Scheduling Using Knowledge-Based Workload Estimation on Grid Environments

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

4 Author(s)
Wen-Chung Shih ; Inst. of Comput. Sci., Nat. Chiao Tung Univ., Hsinchu ; Chao-Tung Yang ; Chun-Jen Chen ; Shian-Shyong Tseng

Parallel loop scheduling on grid environments is a challenging problem, especially for loops with irregular workload distribution. In the past, this problem of load imbalance resulting from irregular workload was not explicitly addressed. This paper proposes a new approach to schedule loop iterations with irregular workload on grid environments. Based on knowledge-based estimation of workload, the proposed method can dispatch an appropriate proportion of workload to each node for execution according to its performance. In addition, the scheduler uses historical statistics of CPU usage and network bandwidth to estimate the dynamically changing performance of each node. Two applications, regular type and irregular one respectively, are implemented and executed on a grid test-bed, which consists of four schools. Experimental results show that the new approach improves the performance on previous schemes

Published in:

Applications and the Internet, 2007. SAINT 2007. International Symposium on

Date of Conference:

Jan. 2007