Performance Evolution of M2M Networks with Improved Particle Swarm Optimization Algorithm

Abstract

Due to heavy M2M traffic, congestion occurs in the network. To solve this problem, an efficient clustering protocol is used called an improved particle swarm optimization (IPSO) algorithm. An improved PSO algorithm is proposed to achieve the optimum solution. First the optimization problem and algorithm parameters are initialized. The fitness value is calculated and each step influences the velocity of each particle towards its pbest and gbest positions. To avoid the algorithm falling into a local optimum, improved particle swarm optimization algorithm is used which modifies the inertial weight so as to avoid particles being trapped in local optima. Finally, the proposed method will be shown in simulations by improving energy efficiency and also by minimizing the overall energy consumption and balancing energy consumption among the nodes during the network lifetime.