Greedy discrete particle swarm optimization based routing protocol for cluster-based wireless sensor networks

Energy efficient routing in wireless sensor networks (WSNs) has been studied widely to enhance the network performance. Various nature-inspired routing mechanisms are proposed to achieve scalable solutions. However, conventional nature-inspired optimization algorithms are insufficient to solve discrete routing optimization problems. In this study, a new discrete particle swarm optimization algorithm (PSO) based routing protocol is designed to achieve better performance. In the new protocol, firstly, two new fitness functions with energy awareness for clustering and routing are formulated respectively. Secondly, a novel greedy discrete PSO with memory (GMDPSO) is put forward to build optimal routing tree. In GMDPSO, particle’s position and velocity are redefined under a discrete scenario; particle update rules are reconsidered based on the network topology; a greedy search strategy is designed to drive particles to find better positon quickly. Besides, searching histories are memorized to accelerate convergence. Simulations results show the efficiency and effectiveness of the new protocol.