Towards Bio-Inspired Self-Organization in Sensor Networks: Applying the Ant Colony Algorithm

Abstract

Self-organization is the key to implement self-calibration, autonomously coordination and P2P communication in sensor networks. Current researches mainly solve this problem in an inappropriate pre-planned manner. The swarm intelligence of the ant colony algorithm (ACA) provides a novel and efficient method for self-organization. For the similarity of sensor network and ant colony, we argue that the sensor networks will benefit from the bio-inspired self-organization by applying the ACA in optimization, structure formation and task/resource allocation. In this paper we outline the current researches on the ACA in sensor network first, then propose the potential applications and research issues. General design of the ACA in sensor network and some challenges are presented as well.