An efficient technique for a series of virtual topology reconfigurations in WDM optical networks

  • Authors:
  • Sungwoo Tak;Passakon Prathombutr;E. K. Park

  • Affiliations:
  • Department of Computer Science and Engineering/Research Institute of Computer Information and Communication, Pusan National University, 30, Jangjeon-dong, Geumjeong-gu, Busan 609-735, Republic of ...;NECTEC, 112 Thailand Science Park, Phahon Yothin Rd., Klong Luang, Pathumthani 12120, Thailand;School of Computing and Engineering, University of Missouri - Kansas City, MO, USA

  • Venue:
  • Computer Communications
  • Year:
  • 2007

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Abstract

This paper studies a series of reconfiguration processes corresponding to a series of traffic demand changes in WDM optical networks. This study describes the reconfiguration problem from two perspectives. First, the reconfiguration problem is a multi-optimization problem such that a single-objective optimization method could not be applied. Second, the reconfiguration problem consists of a series of reconfiguration processes for given traffic demand changes. The current virtual topology optimally generated for a given traffic demand change may lead to the costly disruption of traffic routing to adapt a new traffic demand change because it is independent of the next traffic demand change. Since the reconfiguration process that considers the only current traffic demand cannot guarantee the optimal average outcome in the long term, sequential decision-making is required to optimize the average outcome from the entire series of reconfiguration processes. The proposed reconfiguration technique is to minimize costly changes of lightpath routing changes in terms of network cost and minimize the average hop distance of traffic in terms of network performance simultaneously. Since the objective goal of maximizing network performance conflicts with that of minimizing network cost, there exists a set of non-dominated solutions called the Pareto front. The reconfiguration technique includes a reconfiguration process and a reconfiguration policy. The reconfiguration process finds a set of non-dominated solutions using the PEAP (Pareto Evolutionary Algorithm adapting the Penalty method) that optimizes objective functions by using the concept of Pareto optimal. Then, reconfiguration policy picks a solution from the set of non-dominated solutions using the MDA (Markov Decision Action). A case study based on simulation experiments is conducted to illustrate the application and efficiency of the proposed technique. It shows that our reconfiguration technique incorporating the PEAP and the MDA yields efficient performance in the entire series of reconfiguration processes.