Model for Performance Improvement of Blocking Probability in GMPLS Networks

Abstract

Abstract Generalized multiprotocol Label Switching (GMPLS) is a set of rules which is used in various layers like the Wavelength Division Multiplexing (WDM) layer, Time Division Multiplexing (TDM) layer, etc. to generalize the concepts of labels of Multiprotocol Label Switching networks. A block in call occurs when number of requests is more than the servers and waiting rooms. This call blocking is the very important parameter and can be calculated in terms of probability. There are a number of models to calculate the call blocking probability like Erlang B, Erlang C, etc. This paper suggests a novel, efficient and less – complex model which minimize the call blocking to very much extent for GMPLS networks. This model deals with the factors like number of wavelengths, number of links, traffic intensity, etc. which can help in reducing the call blocking probability and give better results. In this paper, the call-blocking probability is also compared with number of links by considering different wavelengths. A comparison of call-blocking probability of proposed model is also analysed. This paper deals with blocking probability optimization in GMPLS Networks using Fredericks approach. We have used peakedness factor from Fredericks approach in Engset’s formula for this optimization.”