By Topic

Balanced Job Assignment Based on Ant Algorithm for Computing Grids

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

3 Author(s)
Ruay-Shiung Chang ; Nat. Dong Hwa Univ., Hualien ; Jih-Sheng Chang ; Po-Sheng Lin

Grid computing is a new research subject. The computing power and storage space of grids is collected from heterogeneous or homogeneous resources in order to support complicated computing problems. Job scheduling in computing grid is a very important problem. Current scientific applications become more complex and need huge computing power and storage space. It may take a very long time to complete a complicated job. However, to utilize grids, we need an efficient job scheduling algorithm to assign jobs to resources in grids. In this paper, we propose a Balanced Ant Colony Optimization (BACO) algorithm for job scheduling in the Grid environment. There are two schemes introduced in this paper regarding local and global pheromone update. The main contributions of our work are to balance the entire system load and minimize the makespan of a given set of jobs. Compared with the other proposed algorithms, BACO can outperform them according to the experimental results.

Published in:

Asia-Pacific Service Computing Conference, The 2nd IEEE

Date of Conference:

11-14 Dec. 2007