Master-Slave Parallel Genetic Algorithm Based on MapReduce Using Cloud Computing

Abstract:

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The implementation platforms of parallel genetic algorithms (PGAs) include high performance computer, cluster and Grid. Contrast with the traditional platform, a Master-slave PGA based on MapReduce (MMRPGA) of cloud computing platform was proposed. Cloud computing is a new computer platform, suites for larger-scale computing and is low cost. At first, describes the design of MMRPGA, in which the whole evolution is controlled by Master and the fitness computing is assigned to Slaves; then deduces the theoretical speed-up of MMRPGA; at last, implements MMRPGA on Hadoop and compares the speed-up with traditional genetic algorithm, the experiment result shows MMRPGA can achieve slightly lower linear speed-up with Mapper’s number.

Info:

Periodical:

Edited by:

Dongye Sun, Wen-Pei Sung and Ran Chen

Pages:

4023-4027

DOI:

10.4028/www.scientific.net/AMM.121-126.4023

Citation:

G. M. Li et al., "Master-Slave Parallel Genetic Algorithm Based on MapReduce Using Cloud Computing", Applied Mechanics and Materials, Vols. 121-126, pp. 4023-4027, 2012

Online since:

October 2011

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Price:

$35.00

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