By Topic

Investigating of probabilistic load balancing algorithms in grid computing

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)
Nikkhah, M. ; Comput. Sci., Islamic Azad Univ., Fars, Iran ; Safaeipour, R. ; Moradi, M.

The computing grid is a distributed parallel processing system that share and choosing resources dynamically and provide need of user operation power, cost and quality. Grid management resources does as a diagnostic and assigning resources scheduling and resource monitoring in grid. Scheduling process directs tasks to suitable resources. It must take place somehow that load work distributed equally on resources to get the maximum interest out of existed resource, establishing load balancing is one the important performance factors in grid resource management efficiency. in this paper, a model in accordance with tree and probabilistic scheduling algorithms with load balancing purpose was suggested, that in this algorithm class of work, cost, deadline and herd behavior have considered. We investigate the probability of a resource success in different algorithms in accordance with complete time, execute time and cost. Probabilistic algorithms chooses the resources that have better past and leave the duties to it, in case of execution or non-execution on the resource the source will give a reward or punishment.

Published in:

Education Technology and Computer (ICETC), 2010 2nd International Conference on  (Volume:4 )

Date of Conference:

22-24 June 2010