Optimal node deployment strategy for wireless sensor networks based on dynamic ant colony algorithm

Abstract

Sensor networks node deployment has long been a key problem in the research of wireless sensor networks. In order to reduce the cost of sensor deployment, this paper has proposed an optimised strategy for wireless sensor networks node deployment on the basis of dynamic ant colony algorithm, aiming at solving the problem of slow evolution and falling into local optimal solution frequently. The novel algorithm, DACA, features the integration of dynamic heuristic factor, expectations heuristic factor, dynamic evaporation factor, the optimal pheromone global updating strategy and the worst pheromone global updating strategy to improve ant colony algorithm. Then greedy strategy is introduced according to distribution of monitored nodes to make the algorithm more robust to environment changes. A large number of simulation results have proved the effectiveness of this algorithm and showed that the novel algorithm reduces the number of deployed nodes in the network for guaranteed connectivity and coverage.