SBMT: Steiner backup multicast tree

  • Authors:

  • W.-H. Hsu;J. Chen;S.-T. Sheu;C.-F. Chao

  • Affiliations:

  • Department of Computer Science and Information Engineering, Ming Chuan University, Tao-Yuan, Taiwan, R.O.C.;Department of Computer Science and Information Engineering, Chang Gung University, Tao-Yuan, Taiwan, R.O.C.;Department of Electrical Engineering, Tamkang University, Tamsui, Taiwan, R.O.C.;Department of Computer Science and Information Engineering, Tamkang University, Tamsui, Taiwan, R.O.C.

  • Venue:
  • International Journal of Computers and Applications
  • Year:
  • 2006

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Abstract

In the backbone network, a Steiner multicast tree (SMT) will be established for multicast members to minimize the traffic load on networks. However, a communication link or node may fail due to some accidental factors during the transmission period. Downstream nodes with respect to the failed link/node will be forced to leave this tree. In order to guarantee the quality of service (QoS), it is desirable to have some schemes for the multicast tree so that such termination of service can be avoided, or at least reduced. In this paper, we propose a fixed SMT algorithm (FSA) to construct the Steiner backup multicast tree (SBMT). Based on FSA, for each "critical" path, an alternate route with enough bandwidth will be reserved such that most fatal failures in the network can be recovered immediately. The determination of critical paths is based on statistical analysis. In addition, an adaptive SMT algorithm (ASA) is proposed to construct both SMT and SBMT on unreliable networks. The adjustment of the SBMT when nodes dynamically join or leave the SMT is also discussed. The degree of fault tolerance of the proposed strategies is evaluated and compared by simulation. Simulation results demonstrate that FSA and ASA improve the reliability in stable and unstable networks, respectively. Moreover, the dynamic joining process of a node will be sped up by taking both SMT and SBMT into consideration. Simulation results are presented to demonstrate the effectiveness of the optimization.