Abstract
In cloud computing systems, a lot of tasks and data need to deal with. However, processing these tasks and data need resources, which distribute in different position all over the world. To more effectively processing it, finding the optimal data placement makes the processing cost and the transforming time minimum. In this paper, we formulate a model for data placement in cloud computing, propose a particle swarm algorithm, compare and analyze particle swarm algorithm with crossover, mutation and local search algorithm based on particle swarm. The experimental results show our algorithm is more effective, efficient and suited for cloud computing.
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© 2012 Springer-Verlag London Limited
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Guo, L., Zhao, S., Shen, S., Jiang, C. (2012). A Particle Swarm Optimization for Data Placement Strategy in Cloud Computing. In: Zhu, R., Ma, Y. (eds) Information Engineering and Applications. Lecture Notes in Electrical Engineering, vol 154. Springer, London. https://doi.org/10.1007/978-1-4471-2386-6_123
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DOI: https://doi.org/10.1007/978-1-4471-2386-6_123
Publisher Name: Springer, London
Print ISBN: 978-1-4471-2385-9
Online ISBN: 978-1-4471-2386-6
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