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A Hybrid Genetic Algorithm/Variable Neighborhood Search Approach to Maximizing Residual Bandwidth of Links for Route Planning

  • Gajaruban Kandavanam
  • Dmitri Botvich
  • Sasitharan Balasubramaniam
  • Brendan Jennings
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5975)

Abstract

This paper proposes a novel approach to performing residual bandwidth optimization with QoS guarantees in multi-class networks. The approach combines the use of a new highly scalable hybrid GA-VNS algorithm (Genetic Algorithm with Variable Neighborhood Search) with the efficient and accurate estimation of QoS requirements using empirical effective bandwidth estimations. Given a QoS-aware demand matrix, experimental results indicate that the GA-VNS algorithm shows significantly higher success rate in terms of converging to optimum/near optimum solution in comparison to pure GA and another combination of GA and local search heuristic, and also exhibits better scalability and performance. Additional results also show that the proposed solution performs significantly better than OSPF in optimizing residual bandwidth in a medium to large sized network.

Keywords

Feasible Region Variable Neighborhood Search Internet Service Provider Link Utilization Local Search Heuristic 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Gajaruban Kandavanam
    • 1
  • Dmitri Botvich
    • 1
  • Sasitharan Balasubramaniam
    • 1
  • Brendan Jennings
    • 1
  1. 1.TSSGWaterford Institute of TechnologyIreland

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