A novel approach to load balancing problem

Authors:
Chuleui Hong;Wonil Kim;Yeongjoon Kim
Affiliations:
Software School, Sangmyung University, Seoul, Korea;Dept. of Digital Contents, College of Electronics and Information Engineering, Sejong University, Seoul, Korea;Software School, Sangmyung University, Seoul, Korea
Venue:
CIS'04 Proceedings of the First international conference on Computational and Information Science
Year:
2004

Citing 2
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Abstract

In this paper, we propose a novel approach to the load balancing problem, which is an important issue in parallel processing. The proposed load balancing algorithm called Mean Field Genetic Algorithm (MGA) is a hybrid algorithm of Mean Field Annealing (MFA) and Simulated annealing-like Genetic Algorithm (SGA). The proposed MGA combines the benefit of rapid convergence property of MFA and the effective genetic operations of SGA. Our experimental results indicate that the composition of heuristic mapping methods improves the performance over the conventional ones in terms of communication cost, load imbalance and maximum execution time.