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Prediction‐based survivable virtual network mapping against disaster failures

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  • Ying Wang
  • Xiao Liu
  • Xuesong Qiu
  • Wenjing Li

Abstract

Survivable virtual network mapping (SVNM) guarantees that the mapped virtual network works normally against substrate failures. Most of the existing solutions are mainly focusing on single node or single link failure. A long‐standing challenge in SVNM is to reduce the capacity loss of network when substrate failures happen. Because some regions are frequently attacked by disasters, the disaster failures should be paid attention to. In this paper, we re‐consider the existing work on the SVNM and explore the feasible solution of SVNM against disaster failures. We first design the disaster failure model with the knowledge of risk assessment. Then we formulate the problem with the mixed integer programming. Two heuristic algorithms based on the prediction mechanism are proposed. Simulations show that our algorithms increase the average acceptance ratio and reduce the risk of capacity loss in the initial mapping phase compared with previous algorithms. Copyright © 2016 John Wiley & Sons, Ltd.

Suggested Citation

  • Ying Wang & Xiao Liu & Xuesong Qiu & Wenjing Li, 2016. "Prediction‐based survivable virtual network mapping against disaster failures," International Journal of Network Management, John Wiley & Sons, vol. 26(5), pages 336-354, September.
    • Handle: RePEc:wly:intnem:v:26:y:2016:i:5:p:336-354
    DOI: 10.1002/nem.1939
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