Random waypoint impact on bio-inspired routing protocols in WSN

Abstract

Lorem ipsum dolor sit amet, consectetuer adipiscing elit. Etiam lobortis facilisis sem. Nullam nec mi et neque pharetra sollicitudin. Praesent imperdiet mi nec ante. Donec ullamcorper, felis non sodales commodo, lectus velit ultrices augue, a dignissim nibh lectus placerat pede. Vivamus nunc nunc, molestie ut, ultricies vel, semper in, velit. Ut porttitor. Praesent in sapien. Lorem ipsum dolor sit amet, consectetuer adipiscing elit. Duis fringilla tristique neque. Sed interdum libero ut metus. Pellentesque placerat. Nam rutrum augue a leo. Morbi sed elit sit amet ante lobortis sollicitudin. Praesent blandit blandit mauris. Praesent lectus tellus, aliquet aliquam, luctus a, egestas a, turpis. Mauris lacinia lorem sit amet ipsum. Nunc quis urna dictum turpis accumsan semper. Depending on the application requirements, wireless sensor networks (WSNs) are composed by static or mobile sensor nodes. The weaknesses of sensors with mobility arise major challenges especially in routing. Routing in WSNs is among the NP-hard optimization problem that requires efficient and robust methods such as metaheuristics. The ant colony optimization (ACO) and the particle swarm optimization (PSO) are the most used metaheuristics for solving this problem in static WSNs. For dynamic WSNs, the model random waypoint (RWP) is widely proposed to evaluate the performance of mobile networks. In this work, we present a new evaluation of the RWP model impact on the ACO and the PSO-based routing protocols for WSNs, using different parameters like the number of nodes, simulation time and simulation area. Further, this study compares the performance of the ACO and the PSO routing protocols for mobile WSNs.