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.
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© 2004 Springer-Verlag Berlin Heidelberg
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Hong, C., Kim, W., Kim, Y. (2004). A Novel Approach to Load Balancing Problem. In: Zhang, J., He, JH., Fu, Y. (eds) Computational and Information Science. CIS 2004. Lecture Notes in Computer Science, vol 3314. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30497-5_30
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DOI: https://doi.org/10.1007/978-3-540-30497-5_30
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-24127-0
Online ISBN: 978-3-540-30497-5
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