Abstract
Network function virtualization (NFV) is an emerging network paradigm that will ease the network reconfiguration and evolution for Network Service Providers (NSPs). In NFV, the virtual network function placement (VNFP) problem has become a hot topic. However, little research attention has been paid to multicast-oriented VNFP (MVNFP) problem. This paper studies the MVNFP problem and presents a two-step approach to address it. The first step constructs a multicast tree for a given multicast service request and the second one places VNFs onto the tree. In the first step, Dijkstra’s algorithm is adopted while in the second step, a modified genetic algorithm (mGA) with problem-specific chromosome encoding, crossover and mutation is proposed. Simulation results show that mGA performs better than a number of evolutionary algorithms with respect to the solution quality and convergence.
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References
ETSI: Network Functions Virtualisation; Architectural Framework. Standard no. GS NFV 002 v1.1.1. ETSI (2013)
Cohen, R., Lewin-Eytan, L., Naor, J.S.: Near optimal placement of virtual network functions. In: Conference on Computer Communications, pp. 1346–1354. IEEE (2015)
Khebbache, S., Hadji, M., Zeghlache, D.: Scalable and cost-efficient algorithms for VNF chaining and placement problem. In: Innovations in Clouds, Internet and Networks, pp. 92–99. IEEE (2016)
Rankothge, W., Le, F., Russo, A., Lobo, J.: Optimizing resources allocation for virtualized network functions in a cloud center using genetic algorithms. IEEE Trans. Netw. Serv. Manage. 14(2), 343–356 (2017)
Zhang, S.Q., Zhang, Q., Bannazadeh, H.: Routing algorithms for network function virtualization enabled multicast topology on SDN. IEEE Trans. Netw. Serv. Manage. 12(4), 580–594 (2015)
Xu, Z., Liang, W., Huang, M.: Approximation and online algorithms for NFV-enabled multicasting in SDNs. In: International Conference on Distributed Computing Systems, pp. 625–634. IEEE (2017)
Beasley, D., Bull, D., Martin, R.: An introduction to genetic algorithms. Artif. Life 3(1), 63–65 (1999)
Batagelj, V., Brandes, U.: Efficient generation of large random networks. Phys. Rev. E Stat. Nonlin. Soft Matter Phys. 71(3), 036113 (2005)
Xu, L., Luan, Y., Cheng, X., et al.: WCDMA data based LTE site selection scheme in LTE deployment. In: 1st International Conference on Signal and Information Processing, Networking and Computers, pp. 249–260. CRC Press Taylor & Francis Group, Beijing (2015)
Xu, L., Cheng, X., et al.: Mobility load balancing aware radio resource allocation scheme for LTE-advanced cellular networks. In: 16th IEEE International Conference on Communication Technology, pp. 806–812. IEEE Press, Hangzhou (2015)
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Wang, X., Xing, H., Yang, H. (2019). On Multicast-Oriented Virtual Network Function Placement: A Modified Genetic Algorithm. In: Sun, S., Fu, M., Xu, L. (eds) Signal and Information Processing, Networking and Computers. ICSINC 2018. Lecture Notes in Electrical Engineering, vol 550. Springer, Singapore. https://doi.org/10.1007/978-981-13-7123-3_49
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DOI: https://doi.org/10.1007/978-981-13-7123-3_49
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