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A heuristic survivable virtual network mapping algorithm

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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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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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Authors and Affiliations

  1. School of Information Science and Engineering, Shandong Normal University, Jinan, 250014, People’s Republic of China

    Xiangwei Zheng, Jie Tian, Xiancui Xiao & Xiaomei Yu

  2. Shandong Provincial Key Laboratory for Distributed Computer Software Novel Technology, Jinan, 250014, People’s Republic of China

    Xiangwei Zheng, Jie Tian, Xiancui Xiao & Xiaomei Yu

  3. School of Computer Science and Technology, Qufu Normal University, Rizhao, 276826, People’s Republic of China

    Xinchun Cui

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  1. Xiangwei Zheng
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  2. Jie Tian
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  3. Xiancui Xiao
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  4. Xinchun Cui
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  5. Xiaomei Yu
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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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