Sensor´s optimization scheduling based on improved Double-Particle Swarm Optimization (DPSO) algorithm

In order to improve optimization performance of Double-Particle Swarm Optimization (DPSO) algorithm, an Improved Double-Particle Swarm Optimization (IDPSO) algorithm is proposed and applied to the sensor´s optimization scheduling of wireless sensor network (WSN). Adaptive inertia coefficient, time-varying synchronous study factor and speed variability factor are introduced into IDPSO algorithm so as to increase the diversity of species group and improve the ability of global optimization. Based on IDPSO algorithm, selected the sensor resource allocation model of wireless sensor network as the objective function, The experiment has been proved that IDPSO algorithm can obtain more ideal sensor´s resource allocation than DPSO algorithm.