Research On Node Localization Algorithm Based On Ant Colony Optimization For Wireless Sensor Networks

Wireless sensor network is a monitoring system built by a large number of sensor nodes in the way of self-organization and widely used to monitor the information of target area in real time. There are lots of Wireless Sensor Network applications currently. For many applications of wireless sensor networks the information gathered by unknown nodes is generally useless. It is very necessary to obtain the position information of each node in wireless sensor networks. Therefore, node localization plays an extremely important role in applications of wireless sensor networks. At present, the node localization has become a hot topic of the academic research.There are mainly two kinds of node localization algorithms:Range-based localization algorithm and Range-free localization algorithm. Range-based localization algorithm needs to configure additional hardware devices on nodes to measure the distance between nodes. This kind of algorithm has high-precision positioning results, but it increases the cost and energy consumption of the network and shortens the service life of the network. In comparison, Range-free localization algorithm is more simple and convenient to implement while it does not need additional hardware devices. Through the communication between nodes, the location of unknown nodes can be roughly estimated, but the positioning accuracy is not as good as the former.ACO (Ant Colony Optimization) has a good effect in the field of combinatorial optimization as a branch of artificial intelligence. In this paper, the node localization problem is converted into a function optimization problem. ACO is applied in the node localization problem and ACOL(node Localization algorithm based on Ant Colony Optimization) is proposed in this paper. Due to the limitation that ACO easily leads to the prematurity or stow convergence speed, an improved algorithm based on ACO, Adaptive Ant Colony Optimization(AACO), is proposed in this paper. AACO is applied in the node localization problem and AACOL(node Localization algorithm based on the Adaptive Ant Co tony Optimization) is formed to avoid the prematurity and slow convergence speed.Finally, experimental analysis is done by MATLAB simulation software. It compared the positioning accuracies of DV-Hop algorithm, ACOL algorithm and AACOL algorithm under the same experimental environment. The experimental results show that, compared with DV-Hop algorithm, localization accuracy is significantly improved by no matter ACO algorithm or AACO algorithm. The results of AACOL algorithm are much more stable than that of ACOL algorithm.