Balance Particle Swarm Optimization and gravitational search algorithm for energy efficient in heterogeneous wireless sensor networks


In this paper, we propose a Balanced PSOGSA algorithm by combining the ability for social thinking in Particle Swarm Optimization with the local search capability of Gravitational Search Algorithm for reducing the probability of trapping in local optimum and prolonging time period before the death of the first node in wireless sensor network.

Besides, we also improve the objective function to shorten the convergence time of the algorithm. The simulation results show that our proposed protocol has lower energy consumption and longer lifetime compared to other protocols.