Application Of Ant Colony Algorithm In Wireless Sensor Network Routing Protocol

With the continuous development of modern information technology, the wireless sensor networks are increasingly playing an important role in people’s daily lives, and their use has been involved in military, medical, environmental and many other fields. The three important functions of wireless sensor network include data acquisition, data processing and data transmission, which are made up of a large amount of stationary sensor nodes through a self-organization and multi-hop composition ways, the core technology of wireless sensor network is how to select a reasonable and efficient routing, which is an important basis for decision overall network performance. In recent years,(LEACH—Low Energy Adaptive Clustering Hierarchy),(TEEN—Threshold Sensitive Energy Efficient Sensor-Network Protocol),(DD—Directed Diffusion),(Flooding),(SPIN—Sensor Protocol for Information Via Negotiation) and other traditional routing protocols often can not meet the actual needs of the wireless sensor network, so this paper proposes a wireless sensor network routing protocol which is based on an improved ant colony algorithm. The core work of this paper as follows:1、This paper introduces the principle and the scope of the basic ant colony algorithm, summing up that when the basic ant colony algorithm in solving the optimal path problem, although it has a strong ability to find the optimum solution, which is easily falling into a local optimal solution, and meanwhile the convergence time is too long. Considering the lack application of the basic ant colony algorithm in wireless sensor network routing, this paper proposes an improved ant colony algorithm, and applies it to the wireless sensor network routing. This algorithm is not only adding the dynamic penalty function and the weighting factors to the state transition probability formula, but also combining the local pheromone update and global pheromone update’s ways to update the path information, this can be more an efficient and thorough way to find an optimal solution. Preventing the basic ant colony algorithm falling into an local optima solution.2、this algorithm model is not only fully taking into account of the transmission distance from nodes to nodes, but also fully considering the residual energy of the sensor nodes. In order to get an energy efficient communication routing, this paper proposes a smart, dynamic, scalable routing transmission ways.Finally, the simulation results obtain some different curves with the improved ant colony algorithm of Jiao bin Et al, the basic ant colony algorithm and the improved ant colony algorithm of this paper in the residual energy of the sensor nodes and network transmission delay in wireless sensor network routing, the experimental results show that the improved ant colony algorithm of this paper can efficiently reduce the transmission energy consumption among sensor nodes, and meanwhile can efficiently extend the lifetime of the entire network, this algorithm is particularly suitable for a large-scale network structure, because it has a strong scalability.