Abstract
Virtual network mapping (VNM) is a crucial technology for network virtualization to allocate network resource. One of the major challenges for virtual network mapping is the efficient allocation of substrate resources to the virtual networks. In order to further improve the efficiency of the previous algorithms in large scale network, the crossover operator is introduced into discrete particle swarm optimization algorithm, and a hybrid intelligent algorithm is designed. The algorithm can solve the problem that the traditional particle swarm algorithm is easy to fall into local optimal point and is difficult to reach the global optimal. Experimental results show that the algorithm consumes the lowest cost in the case of mapping the same virtual network requests than existing ones, and has higher revenue/costs ratio.
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Acknowledgment
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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Yuan, Y., Peng, S., Zhou, L., Wang, C., Wan, C., Huang, H. (2017). A PSO-Based Virtual Network Mapping Algorithm with Crossover Operator. 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_54
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DOI: https://doi.org/10.1007/978-3-319-52015-5_54
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