Swarm Intelligence-Inspired Adaptive Routing Construction in WSN

The paper presents a heuristic Theoretical Optimal Routing Algorithm(TORA) to achieve location-aided optimal data-gathering structure in wireless sensor networks(WSN). The algorithm´s construction is based on a kind of swarm intelligence mechanism, i.e., ant colony optimization (ACO). The novel design of heuristic factor and pheromone updating rule can endow ant-like agents with the ability of detecting the local energy status of networks to approach the theoretical optimal routing. Via the division of WSN into different functional regions and introduction of energy-efficient weight in heuristic factor, the criterion in routing selection can be adaptively adjusted based on asymmetric power configurations and consumption to improve the robustness of data-routing tree. Finally, simulation results show that the proposed routing scheme can contribute to minimize the total communication energy cost, meanwhile, to enhance the QoS- performance and energy-balance effect in data-gathering.