A particle swarm optimization routing scheme for wireless sensor networks

For the energy consumption problem among nodes in wireless sensor networks (WSNs), a particle swarm optimization routing (PSOR) scheme is proposed in this paper in order to extend the survival time of WSNs. In the previous work, we proposed the LEACH-EA protocol, which considered both residual energy and the influence factor of node distance in selecting cluster heads, and the optimal transmission path was found by the ant colony algorithm. However, since the training data for the LEACH-EA protocol was a randomly generated set of point coordinates, this might cause problems of unstable node coverage and unbalanced data transmission in the network. An improved particle swarm optimization algorithm (IPSO) is introduced to output an optimized set of coordinates while ensuring maximum network connectivity, which sets the inertia weights of the particles to dynamic adaptive values and uses a Monte Carlo method to determine the fitness function. The PSOR scheme and the LEACH-EA protocol are compared in terms of the survival period, energy consumption, node survival rate, and packet forwarding volume of the sensor network. The experimental results show that the PSOR scheme has significantly improved the survival nodes, extended the network life cycle by 30%, and increased the total number of packets by nearly 1.5 times.