The Study Of Ant-Colony Based Routing Algorithm For WSN

Wireless sensor network(WSN) is a hot spot in present research field. Routing protocol is the core in wireless sensor networking. It aims to find the optimal path between the source nodes and the destination nodes, and transmit the data packets correctly along the optimal path. Due to the instinct features of the network nodes, such as limited energy, dynamic topology and data fusion, new challenges and problems are posed for the design of routing protocol in wireless sensor network. So higher requirements of the routing protocols design are proposed.In order to balance the energy consumption, improve the fault tolerance and maximize the lifetime of the network, based on the analyze of classic routing protocols, some ant colony methods are introduced to the design of routing protocols because of their characteristics, including self-organizing, self-adaptive, dynamic parallel optimization searching and positive feedback. It adopts heuristic pheromone allocation strategy according to the objective function. It takes advantages in swarm intelligences through the cooperation of many single limited intelligent ants to carry out the routing algorithm searched by imitating vascular path based on ant colony algorithm.In this work, we studied the features of the human blood vessels and relatedness with the wireless sensor network to explore the enlightenment of building vascular route, and then we studied the dynamic clustering and static clustering models based on the improved ant colony algorithm—Best-Worst Ant System (BWAS) algorithm and discussed its clustering convergence. Thus a vascular routing algorithm base on BWAS is proposed for wireless sensor network, using Particle Swarm Optimization (PSO) clustering method to solve the energy balance clustering. Firstly we make the nodes marked with different grades and do static clustering with different probabilities, and then generated the paths by using BWAS algorithm. The path pheromone values are set to be the probability of transmission path. It established multiple paths and selects the path with the highest probability to be the transmission path.The routing algorithm avoids delay or loss of the data caused by the transmission failure of the nodes or links through the simulations. It also improves the fault tolerance and transmission stability of the network. It balances the energy consumption and maximize lifetime of the network. This work posed innovative and significant in related research field.