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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. © Springer-Verlag Berlin Heidelberg 2007.
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ISSN: 0302-9743
Year: 2007
Volume: 4683 LNCS
Page: 393-400
Language: English
0 . 4 0 2
JCR@2005
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ESI Highly Cited Papers on the List: 0 Unfold All
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30 Days PV: 3
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