Swarm Intelligence for the Self-Organization of Wireless Sensor Network

Abstract

In wireless sensor networks (WSN), it is a fundamental issue to balance two conflicted performance indexes: sensing ability and energy cost, via the self-organization (SO). Here each sensor node in the WSN is mapped to an ant in ant colony system and node communication information is modeled by the current pheromone. The SO problem of the WSN is transformed to the swarm intelligence optimization problem of ant colony. If an ant detects an interested target, it will lay pheromone, which can diffuse in its neighbor zone. The accumulated pheromone is calculated to adaptively and distributively determine the waking probability of the ant so that the self organization of the WSN can be implemented automatically. Hence a new swarm intelligence method for the SO of WSN is proposed. The simulations show the effectiveness of our method.