Abstract
Allocating the underlying physical substrate network resources for users reasonably is the target of virtual network embedding (VNE), which is a hot issue in virtual resource allocation field. In order to prevent the premature convergence and poor performance of local optimization during mapping procedure, in this paper, we combine DPSO, taboo-search technology and simulated annealing algorithms to solve premature convergence problem by using taboo list and annealing process, then propose a virtual network embedding algorithm based on hybrid particle swarm optimization. Simulation results show that our algorithm can improve the revenue to cost ratio and the acceptance ratio.
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Acknowledgement
This work was partially supported by the National Natural Science Foundation of China under Grant Nos. 61300195 and 61379041, the Natural Science Foundation of Hebei Province under Grant Nos. F2014501078 and F2016501079, the Science and Technology Support Program of Northeastern University at Qinhuangdao under Grant No. XNK201401, and the Science and Technology Project of Guangzhou under Grant No. 2013Y2-00069.
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Wang, C., Su, Y., Zhou, L., Peng, S., Yuan, Y., Huang, H. (2017). A Virtual Network Embedding Algorithm Based on Hybrid Particle Swarm Optimization. In: Qiu, M. (eds) Smart Computing and Communication. SmartCom 2016. Lecture Notes in Computer Science(), vol 10135. Springer, Cham. https://doi.org/10.1007/978-3-319-52015-5_58
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DOI: https://doi.org/10.1007/978-3-319-52015-5_58
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