By Topic

A Heuristic Algorithm for Task Scheduling Based on Mean Load

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)
Lina Ni ; Dept. of Comput. Sci., Tongji Univ., Shanghai ; Jinquan Zhang ; Chungang Yan ; Changjun Jiang

Efficient task scheduling is critical to achieving high performance on grid computing environment. A heuristic task scheduling algorithm satisfied resources load balancing on grid environment is presented in this paper. The algorithm schedules tasks by employing mean load based on task predictive execution time as heuristic information to obtain an initial scheduling strategy. Then an optimal scheduling strategy is achieved by selecting two machines satisfied condition to change their loads via reassigning their tasks under the heuristic of their mean load. Methods of selecting machines and tasks are given in this paper to increase the throughput of the system and reduce the total waiting time. The performance of the proposed algorithm is evaluated via extensive simulation experiments. Experiment results show that the heuristic algorithm performs significantly to ensure high load balancing and achieve an optimal scheduling strategy almost all the time. Furthermore, results show that our algorithm is high efficient in terms of time complexity.

Published in:

Semantics, Knowledge and Grid, 2005. SKG '05. First International Conference on

Date of Conference:

27-29 Nov. 2005