Virtual network embedding with opportunistic resource sharing

Sheng Zhang, Zhuzhong Qian, Jie Wu, Sanglu Lu, Leah Epstein

Research output: Contribution to journalArticlepeer-review

Abstract

Network virtualization has emerged as a promising approach to overcome the ossification of the Internet. A major challenge in network virtualization is the so-called virtual network embedding problem, which deals with the efficient embedding of virtual networks with resource constraints into a shared substrate network. A number of heuristics have been proposed to cope with the NP-hardness of this problem; however, all of the existing proposals reserve fixed resources throughout the entire lifetime of a virtual network. In this paper, we re-examine this problem with the position that time-varying resource requirements of virtual networks should be taken into consideration, and we present an opportunistic resource sharing-based mapping framework, ORS, where substrate resources are opportunistically shared among multiple virtual networks. We formulate the time slot assignment as an optimization problem; then, we prove the decision version of the problem to be NP-hard in the strong sense. Observing the resemblance between our problem and the bin packing problem, we adopt the core idea of first-fit and propose two practical solutions: first-fit by collision probability (CFF) and first-fit by expectation of indicators' sum (EFF). Simulation results show that ORS provides a more efficient utilization of substrate resources than two state-of-the-art fixed-resource embedding schemes.

Original languageEnglish
Article number6471977
Pages (from-to)816-827
Number of pages12
JournalIEEE Transactions on Parallel and Distributed Systems
Volume25
Issue number3
DOIs
StatePublished - Mar 2014

Keywords

  • 3-partition
  • NP-hard
  • Virtual network embedding
  • bin packing
  • opportunistic resource sharing

ASJC Scopus subject areas

  • Signal Processing
  • Hardware and Architecture
  • Computational Theory and Mathematics

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