To solve the problems of poor correlation in node mapping and link mapping, wide apart of adjacent virtual node during mapping and imbalance resource consumption of nodes with their adjacent links, a two-stage Virtual Network Mapping algorithm is proposed based on Node Adjacent-awareness and Path comprehensive evaluation (NA-PVNM). In the stage of node mapping, firstly, virtual nodes are ranked according to resources request and breadth-first search, secondly, a node fitness function is set to find the best node in candidates of a virtual node, which takes resource richness and topology connection feature into account. In the stage of link mapping, a path fitness function is set to find the best path in candidates, which takes available bandwidth, node resource and hops of path into account. Simulation results show that the path distances of virtual links are reduced, the acceptance ratio and revenue/cost ratio of virtual networks are improved using the proposed NA-PVNM algorithm. The influence of location constraint and substrate topology feature on algorithm performance, and the resource occupancy of substrate network during mapping are analyzed by experiments. Experimental results show that, under the constraint of physical resource distribution and virtual network requests, the critical factor of improving success rate is to reduce resource consumption during mapping.
WANG A, IYEN M, DUTTA R, et al. Network virtualization: Technologies, perspectives, and frontiers[J]. Journal of Lightwave Technology, 2013, 31(4): 523-537.
[2]
ANDERSON T, PETERSON L, SHENKER S, et al. Overcoming the Internet impasse through virtualization[J]. Computer, 2005, 38(4): 34-41.
[3]
YU M L, YI Y, REXFORD J, et al. Rethinking virtual network embedding: Substrate support for path splitting and migration[J]. ACM SIGCOMM Computer Communication Review, 2008, 38(2): 17-29.
[4]
CUI H Y, GAO W J, LIU J, et al. A virtual network embedding algorithm based on virtual topology connection feature[C]. IEEE 16th International Symposium on Wireless Personal Multimedia Communications, Atlantic City, 2013: 1-5.
[5]
HOUDA J and DJAMAL Z. An adaptive load balancing scheme for evolving virtual networks[C]. 12th Annual IEEE Consumer Communications and Networking Conference, Las Vegas City, 2015: 492-498.
[6]
FENG M, LIAO J X, WANG J Y, et al. Topology-aware virtual network embedding based on multiple characteristics [C]. IEEE ICC 2014-Next-Generation Networking Symposium, Sydney City, 2014: 2956-2962.
LIU Guangyuan and SU Sen. The research of reliable virtual network mapping algorithm[J]. Acta Electronica Sinica, 2016, 44(8): 1820-1825. doi: 10.3969/j.issn.0372-2112.2016.08.007.
[9]
DING J, HUANG T, LIU J, et al. Virtual network embedding based on real-time topological attributes[J]. Frontiers of Information Technology & Electronic Engineering, 2015, 16(2): 109-118. doi: 10.1631/FITEE.1400147.
[10]
GONG L, WEN Y, ZHU Z, et al. Toward profit-seeking virtual network embedding algorithm via global resource capacity[C]. Proceedings of IEEE INFOCOM, Toronto, 2014: 1-9.
[11]
NASHIKD S, REAZ A, SHIHABUR R C, et al. Connectivity- aware virtual network embedding[C]. IEEE 8th IFIP International Conference on New Technologies, Mobility and Security, Cyprus City, 2016: 46-54.
[12]
BECK M T, LINNHOFF P C, FISCHER A, et al. A simulation framework for virtual network embedding algorithms[C]. Proceedings of the IEEE Telecommunications Network Strategy and Planning Symposium (Networks), Madeira Island, Portugal, 2014: 1-6.
[13]
DING J, HUANG T, WANG J, et al. Virtual network embedding through node connectivity[J]. The Journal of China Universities of Posts and Telecommunications, 2015, 22(1): 17-23. doi: 10.1016/S1005-8885(15)60620-3.
GONG Shuiqing, CHEN Jing, and WANG Wei. Energy- aware virtual network embedding algorithm for heterogeneous nodes[J]. Journal of Electronics & Information Technology, 2015, 37(8): 2021-2027. doi: 10.11999/ JEIT141527.
JIA Wei and XIA Jingbo. Research on virtual network embedding across multiple domains[J]. Journal of Electronics & Information Technology, 2016, 38(3): 728-734. doi: 10. 11999/JEIT150656.
[17]
ZHANG Z B, SU S, LIN Y, et al. Adaptive multi-objective artificial immune system based virtual network embedding [J]. Journal of Network and Computer Applications, 2015, 53(1): 140-155. doi: 10.1016/j.jnca.2015.03.007.
[18]
FISCHER A, BOTERO J F, BECK M T, et al. Virtual network embedding: A survey[J]. IEEE Communications Surveys & Tutorials, 2013, 15(4): 1888-1906.