A novel energy efficient converage control in WSNs based on ant colony optimization

Wireless sensor networks is consist of a group of tiny power-constrained devices with functions of sensing, computing and communication. Because of the limited energy and computational resources available to sensor nodes, the number of nodes placement to cover the whole area completely is often important than other things. Coverage effciency depends on the number of active nodes, the more active nodes there are in the network, the higher is the degree of coverage. A novel converage control method based on multi-objective ant colony optimization is proposed in this paper. A more precise probabilistic sensor detection model is used in this scheme. The minimum number of sensor nodes is selected while maintain full coverage. The simulation results show that the algorithm can active the minimum sensor nodes as well as maintaining high coveage rate, and cost less energy consumption and achieve a better performance than other algorithm in the same condition.