Repeatable optimization algorithm based discrete PSO for virtual network embedding

  • Authors:

  • Ying Yuan;Cui-Rong Wang;Cong Wan;Cong Wang;Xin Song

  • Affiliations:

  • School of Information Science and Engineering, Northeastern University, Shenyang, China;School of Computer and Communication Engineering, Northeastern University at Qinhuangdao, Qinhuangdao, China;School of Computer and Communication Engineering, Northeastern University at Qinhuangdao, Qinhuangdao, China;School of Computer and Communication Engineering, Northeastern University at Qinhuangdao, Qinhuangdao, China;School of Computer and Communication Engineering, Northeastern University at Qinhuangdao, Qinhuangdao, China

  • Venue:
  • ISNN'13 Proceedings of the 10th international conference on Advances in Neural Networks - Volume Part I
  • Year:
  • 2013

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Abstract

Aiming at reducing the link load and improving substrate network resource utilization ratio, we model the virtual network embedding (VNE) problem as an integer linear programming and present a discrete particle swarm optimization based algorithm to solve the problem. The approach allows multiple virtual nodes of the same VN can be embedded into the same physical node as long as there is enough resource capacity. It not only can cut down embedding processes of virtual link and reduce the embedding time, but also can save the physical link cost and make more virtual networks to be embedded at the same time. Simulation results demonstrate that comparing with the existing VNE algorithm, the proposed algorithm performs better for accessing more virtual networks and reducing embedding cost.