REDUCTION OF BLOCKING PROBABILITY IN GMPLS OPTICAL NETWORKS USING NOVEL HYBRID OPTIMIZATION ALGORITHM

Abstract

In this paper, an optimized algorithm hybridizing Minimum Execution Time (MET), Weighted Round Robin (WRR) and Particle Swarm Optimization (PSO) is presented to minimize the blocking probability in Generalized Multi-Protocol Label Switched (GMPLS) optical networks to improve Quality of Service (QoS). MET is used for distributing the bandwidth in a well-organized approach to further reduce the latency in the network. The deviation in blocking probability is calculated depending on demanding traffic load and number of wavelengths accessible at the instant when user demand occurs in the GMPLS optical network. WRR is used to increase the flexibility in computing the path between the nodes. The overheads are also optimized using PSO with increasing number of iterations. The consequences exposed that the blocking probability reduces with growing number of accessible wavelengths. The value of blocking probability obtained is <1% by using the proposed hybrid optimization technique for bandwidth allocation and path computation.