An improved particle swarm optimization for data streams scheduling on heterogeneous cluster

Authors:
Tian Xia;Wenzhong Guo;Guolong Chen
Affiliations:
College of Mathematics and Computer Sciences, Fuzhou University, Fuzhou, China;College of Mathematics and Computer Sciences, Fuzhou University, Fuzhou, China;College of Mathematics and Computer Sciences, Fuzhou University, Fuzhou, China
Venue:
ISICA'07 Proceedings of the 2nd international conference on Advances in computation and intelligence
Year:
2007

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Abstract

An improved particle swarm optimization (PSO) algorithm for data streams scheduling on heterogeneous cluster is proposed in this paper, which adopts transgenic operator based on gene theory and correspondent good gene fragments depend on special problem to improve algorithm's ability of local solution. Furthermore, mutation operator of genetic algorithm is introduced to improve algorithm's ability of global exploration. Simulation tests show that the new algorithm can well balance local solution and global exploration and is more efficient in the data streams scheduling.