Intelligent Fish Swarm Inspired Protocol (IFSIP) for Dynamic Ideal Routing in Cognitive Radio Ad-Hoc Networks

Abstract

Poor routing in ad hoc networks affects entire performance that leads to latency and a massive amount of energy consumption. An essential task in Cognitive Radio Ad Hoc Networks (CRAHN) is to discover a better route to the destination from the source where the transmitted data crosses every node in the routing path. In this paper, a novel reactive multicast routing protocol namely Intelligent Fish Swarm Inspired Protocol (IFSIP) proposed to minimize the global latency and energy consumption by finding the best route dynamically. It is difficult to provide a better solution to the issues that arise in route optimization. Routing defines the methodology of selecting the best route. IFSIP aims to find and utilize dynamic ideal routes. By considering service rate and spectrum accessibility, it gradually minimizes congestion on different routes. IFSIP sends data only after checking the quality of route. Optimization of IFSIP helps node to choose the best route. M/G/1 queueing model used to reduce the congestion and provide the service in short. Results indicate IFSIP significantly performs well than other baseline schemes towards finding the best route, minimizing delay and energy consumption. Evaluation of IFSIP conducted with node count and link failure parameters and it is evident that IFSIP has reduced the delay and energy consumption by increasing the throughput and packet delivery ratio.