The Optimization Research Of Wireless Sensor Network Based On Improving Ant Colony Algorithm

Wireless sensor network consists of a large amount of micro sensor node deployed in themonitoring area. It is a self-organized and multi-hop network that transfers data by way ofwireless communication. It has wide prospect of development and has been applied in manyaspects such as military defense, health care, environmental monitoring, business intelligence,etc. Since the energy of the node is limited, traditional routing algorithms could not satisfy theenergy consumption demand. Ant colony algorithm is suitable for solving combinatorialoptimization problems and with strong dynamic adaptability, so it conforms to thecharacteristics of the wireless sensor network. In order to achieve the goals of reducingenergy consumption and keeping energy balance, the paper presents serval optimizationstrategies based on improving ant colony algorithm, so as to prolong the lifetime ofnetwork.The basic ant colony algorithm emphasizes the positive feedback mechanism ofpheromone, and guide algorithm to the evolution of optimal solution. As to wireless sensornetwork, if all the data transmits along the optimal path, the sensor node in the path will befail soon because energy consumption is too fast. Finally it shorten the lifetime of network.This paper combines of the positive feedback and negative feedback mechanism ofpheromone, balances the data flow effectively. In addition, the paper takes use of the adaptiveprobability function based on energy optimization, and the deployment of multiple sinknodes.The paper performs the simulation experiment for testing the improving strategies, withthe comparision of the flooding algorithm and base ant colony algorithm. The result shows theimproving strategies is better than those two algorithm above in aspects of energyconsumption, energy balance and lifetime of network.It verified the effectiveness of theoptimization strategies.