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A heuristic survivable virtual network mapping algorithm

Abstract

Network virtualization is a promising solution to attack Internet ossification. Virtual network mapping (or embedding) problem is the core of it and is proved to be NP-hard. In this paper, virtual network mapping problem with survivability is formulated and solved with a heuristic algorithm. Firstly, network link resources are divided into primary flow resources and secondary flow resources. The former are used under normal network operation, whereas the latter are used as backup resources once the networks fail. Secondly, we introduce a novel metric named global resource capacity (GRC) which is recently proposed for measuring node mapping capacity to improve network load balance. At last, a heuristic survivable virtual network embedding algorithm (GRC-SVNE) is proposed. In node mapping phase, we calculate the mapping capacity of all nodes and then some nodes are selected as candidate nodes for virtual network embedding and the goal is to improve mapping successful ratio. After that, link mapping is performed with Dijkstra algorithm. Simulation results show that GRC-SVNE outperforms the traditional greedy algorithm (GREEDY), randomized algorithm (R-ViNE) as well as deterministic algorithm (D-ViNE) and demonstrates desirable results in terms of acceptance ratio, network load balance and network revenue.

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References

  • Butt NF, Chowdhury M, Boutaba R (2010) Topology-awareness and reoptimization mechanism for virtual network embedding. International conference on research in networking. Springer, Berlin, Heidelberg, pp 27–39

    Google Scholar 

  • Caraguay LV, Villalba LJG (2017) Monitoring and discovery for self-organized network management in virtualized and software defined networks. Sensors 17(4):731

    Article  Google Scholar 

  • Chowdhury M, Rahman MR, Boutaba R (2012) Vineyard: virtual network embedding algorithms with coordinated node and link mapping. IEEE/ACM Trans Netw 20(1):206–219

    Article  Google Scholar 

  • Chowdhury NMMK, Boutaba R (2009) Network virtualization: state of the art and research challenges. IEEE Commun Mag 47(7):20–26

    Article  Google Scholar 

  • Chowdhury NMMK, Boutaba R (2010) A survey of network virtualization. Comput Netw 54(5):862–876

    Article  MATH  Google Scholar 

  • Da XL, He W, Li S (2014) Internet of things in industries: a survey. IEEE Trans Ind Inf 10(4):2233–2243

    Article  Google Scholar 

  • Fajjari I, Aitsaadi N, Pujolle G (2011) Vnr algorithm: a greedy approach for virtual networks reconfigurations. In: Global Telecommunications Conference (GLOBECOM 2011). IEEE, pp 1–6

  • Feamster N, Gao L, Rexford J (2007) How to lease the internet in your spare time. ACM SIGCOMM Comput Commun Rev 37(1):61–64

    Article  Google Scholar 

  • Gao GP, Hu B, Zhang JS (2013) Design of a miniaturization printed circular-slot UWB antenna by the half-cutting method. IEEE Antennas Wireless Propag. Lett. 12(1):567–570

    Article  Google Scholar 

  • Gong L, Wen Y, Zhu Z (2014) Toward profit-seeking virtual network embedding algorithm via global resource capacity. In: Proceedings of the 2014 INFOCOM. IEEE, pp 1–9

  • Gu B, Sheng VS (2017) A robust regularization path algorithm for \(\nu \)-support vector classification. IEEE Trans Neural Netw Learn Syst 28(5):1241–1248

    Article  Google Scholar 

  • Hu Q, Wang Y, Cao X (2013) Resolve the virtual network embedding problem: a column generation approach. In: Proceedings of the 2013 INFOCOM. IEEE, pp 410–414

  • Khan A, Zugenmaier A, Jurca D (2012) Network virtualization: a hypervisor for the internet? IEEE Commun Mag 50(1):136–143

    Article  Google Scholar 

  • Li J, Chen XF, Huang XY, Tang SH (2015a) Secure distributed deduplication systems with improved reliability. IEEE Trans Comput 64(12):3569–3579

    MathSciNet  Article  MATH  Google Scholar 

  • Li J, Li JW, Chen XF (2015b) Identity-based encryption with outsourced revocation in cloud computing. IEEE Trans Comput 64(2):425–437

    MathSciNet  Article  MATH  Google Scholar 

  • Li J, Zhang YM, Chen XF, Xiang Y (2018) Secure attribute-based data sharing for resource-limited users in cloud computing. Comput Secur 72:1–12

    Article  Google Scholar 

  • Lischka J, Karl H (2009) A virtual network mapping algorithm based on subgraph isomorphism detection. In: Proceedings of the ACM workshop on virtualized infrastructure systems and architectures. ACM, pp 81–88

  • Luo J, Chen L, Li RF (2012) A heuristic resource allocation algorithm for virtual network embedding. Sci Sin Inf 42(8):960–973

    Google Scholar 

  • Qiao C, Guo B, Huang S (2011) A novel two-step approach to surviving facility failures. In: Proceedings of optical fiber communication conference and exposition (OFC/NFOEC), pp 1–3

  • Rahman MR, Boutaba R (2013) Svne: survivable virtual network embedding algorithms for network virtualization. IEEE Trans Netw Serv Manage 10(2):105–118

    Article  Google Scholar 

  • Rahman MR, Aib I, Boutaba R (2010) Survivable virtual network embedding. Networking 6091:40–52

    Google Scholar 

  • Soualah O, Fajjari I, Aitsaadi N (2014) A reliable virtual network embedding algorithm based on game theory within cloud’s backbone. In: IEEE international conference on communications, pp 2975–2981

  • Xiao X, Zheng XW (2016) A proposal of survivable virtual network embedding algorithm. J High Speed Netw 22(3):241–251

    Article  Google Scholar 

  • Yu M, Yi Y, Rexford J (2008) Rethinking virtual network embedding: substrate support for path splitting and migration. ACM SIGCOMM Comput Commun Rev 38(2):17–29

    Article  Google Scholar 

  • Zheng XW, Liu H, Wang XG (2013) A virtual network embedding algorithm incorporating biogeography based optimization. In: Proceedings of the joint international conference on pervasive computing and the networked world. Springer, Cham, pp 810–818

  • Zheng XW, Lu DJ, Wang X, Liu H (2015) A cooperative coevolutionary biogeography-based optimizer. Appl Intell 43(1):95–111

    Article  Google Scholar 

  • Zhu Y, Ammar MH (2006) Algorithms for assigning substrate network resources to virtual network components. In: Proceedings of the 2006 INFOCOM, vol 1200. IEEE, pp 1–12

Download references

Acknowledgements

This study was funded by the National Natural Science Foundation of China (61373149, 61672329) and Shandong Provincial Natural Science Foundation for Young Scholars of China (Grant No. ZR2017QF008).

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Correspondence to Xiaomei Yu.

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This article does not contain any studies with human participants or animals performed by any of the authors.

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Communicated by A. Di Nola.

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Zheng, X., Tian, J., Xiao, X. et al. A heuristic survivable virtual network mapping algorithm. Soft Comput 23, 1453–1463 (2019). https://doi.org/10.1007/s00500-018-3152-7

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  • DOI: https://doi.org/10.1007/s00500-018-3152-7

Keywords

  • Heuristic algorithm
  • Network failure
  • Survivability
  • Load balance