By Topic

Dynamic fuzzy load balancing on LAM/MPI clusters with applications in parallel master-slave implementations of an evolutionary neuro-fuzzy learning system

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
$33 $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)
Lotika Singh ; Department of Physics and Computer Science, Dayalbagh Educational Institute, Agra 282005 India ; Apurva Narayan ; Satish Kumar

In the context of parallel master-slave implementations of evolutionary learning in fuzzy-neural network models, a major issue that arises during runtime is how to balance the load-the number of strings assigned to a slave for evaluation during a generation-in order to achieve maximum speed up. Slave evaluation times can fluctuate drastically depending upon the local computational load on the slave (given fixed node specifications). Communication delays compound the problem of proper load assignment. In this paper we propose the design of a novel dynamic fuzzy load estimator for application to load balancing on heterogeneous LAM/MPI clusters. Using average evaluation time and communication delay feedback estimates from slaves, string assignments for evaluation to slaves are dynamically changed during runtime. Extensive tests on heterogenous clusters shows that considerable speedups can be achieved using the proposed fuzzy controller.

Published in:

Fuzzy Systems, 2008. FUZZ-IEEE 2008. (IEEE World Congress on Computational Intelligence). IEEE International Conference on

Date of Conference:

1-6 June 2008