Swarm Based Fault Tolerant Routing in MPLS Networks
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In MPLS/GMPLS networks, during fault prevalence, heavy data loss occurs within minimum duration of time. Also it is difficult to handle these faults as it may cause critical network survivability issue. Most of the existing literature works estimates the failure probability, bandwidth and delay of all routes using the traditional shortest path algorithm which leads to huge delay and overhead. In order to overcome these issues, in this paper, we propose ant colony optimization (ACO) algorithm for routing in GMLPS/MPLS. In this technique, swarm intelligence based fault tolerant routing is performed. This involves the selection of optimal path with maximum available bandwidth and minimum delay. In order to enhance the security of MPLS network, the threshold secret sharing mechanism is considered. By simulation results, we show that the proposed approach minimizes the delay and route failures while increasing the bandwidth utilization and throughput.
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