A hybrid computing approach to improve convergence time for scalable network

Abstract

Border Gateway Protocol (BGP) is a widely used routing protocol in the new era for the inter-communication between the multiple autonomous systems and it has been largely on the internet in all categories of the scalable network. In the event of failure, the BGP as an inter-domain routing protocol shows slow convergence, which results in high considerable delay in several internet/web applications. The minimum route advertisement interval (MRAI) timers are mostly used by network operators to reduce the issues occurring at the time of increasing convergence time. Many researchers have been working on variation in MRAI timer and effect of it on scalability and network convergence. The increasing size of a network leads to an increase in the value of MRAI timers. Hence, keeping the value of MRAI timers optimum results in reducing the issue of slow convergence for the scalable network. The proposed system (FAPSO) reduces the problem of convergence time by incorporating fuzzy logic into Particle Swarm Optimization (PSO) algorithm for the scalable network. In comparison with the static value of MRAI timer i.e., 30 s, FAPSO is a suitable algorithm that gives the optimal value of convergence time for the scalable network.