The Research Of Wireless Sensor Network’s Routing Based On Improved Ant Colony Algorithm

Wireless sensor networks (Wireless Sensor Networks, WSNs) by a large number of micro-sensors, by way of wireless communications to send and receive data. Send a wireless sensor network is a self-organizing network, data from the source node to a single or multiple hops to Sink node. The network has been widely used in military, medical, construction, forestry, there are broad prospects for development. Since the sensor node energy is limited, can’t be replaced to add energy and power, during the establishment of a routing protocol, the traditional routing protocols can’t meet the actual demand. To reduce network energy consumption, energy balancing node, dynamic changes to adapt to the environment, on the basis of ant colony algorithm, an improved ant colony algorithm to optimize routing protocol for wireless sensor networks.Algorithm by dividing the entire area of the network boot ants have directional forwarding, the sensor is capable of forwarding toward the Sink node in forwarding data, to prevent the blind node forwarding node leads to energy waste, effectively balancing nodes energy appears. In addition, the combination of the residual energy evaluation function to guide the ants and the pheromone forwarding, achieve energy efficient and balanced. In addition, in order to prevent excessive energy consumption on a path leading to failure of the path, through the merits of the two route optimization algorithm determines the extent of seeking paths; on top of this, on the Ant node update and forwarding rule, by seeking excellent process pheromone left, which guide the remaining ants choose the optimal path, with fewer iterations to get better performance.In this paper, NS2 simulation tool for improved ant colony algorithm, and the simulation results and flooding algorithm and EEABR algorithm simulation results were compared. By comparison can be drawn, improved ant colony algorithm to reduce energy consumption, has some advantages on the energy balance and to extend the network node effective time.