1st Annual Conference on Broadband Networks

Research Article

Survivable traffic grooming with path protection at the connection level in WDM mesh networks

  • @INPROCEEDINGS{10.1109/BROADNETS.2004.80,
        author={Wang Yao and Byrav Ramamurthy},
        title={Survivable traffic grooming with path protection at the connection level in WDM mesh networks},
        proceedings={1st Annual Conference on Broadband Networks},
        publisher={IEEE},
        proceedings_a={BROADNETS},
        year={2004},
        month={12},
        keywords={},
        doi={10.1109/BROADNETS.2004.80}
    }
    
  • Wang Yao
    Byrav Ramamurthy
    Year: 2004
    Survivable traffic grooming with path protection at the connection level in WDM mesh networks
    BROADNETS
    IEEE
    DOI: 10.1109/BROADNETS.2004.80
Wang Yao1,*, Byrav Ramamurthy1,*
  • 1: Department of Computer Science and Engineering, University of Nebraska-Lincoln
*Contact email: wyao@cse.unl.edu , byrav@cse.unl.edu

Abstract

Survivable traffic grooming (STG) is a promising approach to provide reliable and resource-efficient multigranularity connection services in wavelength division multiplexing (WDM) optical networks. In this paper, we study the STG problem in WDM mesh optical networks employing path protection at the connection level. Both dedicated protection and shared protection schemes are considered. Given the network resources, the objective of the STG problem is to maximize network throughput. To enable survivability under various kinds of single failures such as fiber cut and duct cut, we consider the general shared risk link group (SRLG) diverse routing constraints. We first resort to the integer linear programming (ILP) approach to obtain optimal solutions. To address its high computational complexity, we then propose three efficient heuristics, namely separated survivable grooming algorithm (SSGA), integrated survivable grooming algorithm (ISGA) and tabu search survivable grooming algorithm (TSGA). While SSGA and ISGA correspond to an overlay network model and a peer network model respectively, TSGA further improves the grooming results from SSGA and ISGA by incorporating the effective tabu search method. Numerical results show that the heuristics achieve comparable solutions to the ILP approach, which uses significantly longer running times than the heuristics.