Wireless sensor network node optimal coverage based on improved genetic algorithm and binary ant colony algorithm

Considering the situation of some practical factors such as energy saving of the nodes and the high density of distributing nodes in wireless sensor networks, a wireless sensor network (WSN) node optimal coverage method based on improved genetic algorithm and binary ant colony algorithm is proposed in this paper. The genetic algorithm and ant colony algorithm are improved and fused aiming at their disadvantages. The binary code expects a low intelligence of each ant, and each path corresponds to a comparatively small storage space, thus considerably improving the efficiency of computation. The optimal working node set is computed according to the max-coverage area of working sensor and the min-number of working sensor constraint conditions to optimize algorithm. The simulation results demonstrate that the proposed algorithm can converge at the optimal solution fast and satisfy the requirement of low node utilization rate and a high coverage rate, thus prolonging the network lifetime efficiently.