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Wireless sensor network location problem is one of hot focus in the academic community recently and DV-Hop algorithm is commonly used to solve the typical location algorithms in wireless sensor Network. In order to improve the efficiency of the DV-Hop algorithm, ant colony algorithm and particle swarm optimization have been brought into DV-Hop algorithm for optimizing globally. The AP-DV-Hop algorithm makes use of the advantages of ACA and PSO so as to guarantee the globality of optimal solutions which avoids trapping in local optimum with the help of the particle nature of ant agents and initialized random solutions. Finally, the simulation experiment results have shown that AP-DV-Hop algorithm has smaller average location error than DV-Hop algorithm and genetic algorithm. Introduction Wireless sensor network (WSN) is a monitoring system composed of lots of sensor nodes in a self organizing way, which is applied widely to monitor and record the real-time conditions of the target area, such as temperature, decibel, humidity, ultraviolet light, PM2.5 and so on [1]. In the wireless sensor network, the sensor nodes without exact locations are called unknown sensor nodes. The information recorded by unknown sensor nodes is unusable because of the absence of exact locations information. So in the wireless sensor network, the sensor node location algorithm plays an important role which has become the hot focus in the academic community recently. All of the sensor node location algorithms could be classified into two categories: Range-based location algorithm and Range-free location algorithm. Range-based location algorithm which has higher precision level, needs to configure additional hardware devices on sensor nodes to measure the distance between any pair of nodes. So as to the cost and energy consumption of WSN are also much more. In contrast, it is easy for Range-free location algorithm with no need for additional hardware devices to estimate the location of unknown sensor nodes [2]. But the low precision level of results is the mainly disadvantage of Range-free location algorithm. It is universally acknowledged that the DV-Hop algorithm which estimate the distance between the anchor node and unknown node according to hops is one of the most effective Range-free location algorithms. To improve the efficiency of the DV-Hop algorithm, ant colony algorithm and particle swarm optimization usually are usually used for optimizing globally. In this paper an improved DV-Hop algorithm based on ant colony algorithm and particle swarm optimization (AP-DV-Hop) has been presented for solving wireless sensor network location problem. In order to improve the performance and precision of DV-Hop algorithm, ant colony algorithm and particle swarm optimization are used to minimize the fitness function of DV-Hop, so as to optimize the results of DV-Hop according to different distance or paths. Finally, the simulation experiment reflects that the AP-DV-Hop algorithm have lower average location error and higher location precision than DV-Hop algorithm.

Improved DV-Hop Algorithm Based on Ant Colony Algorithm and Particle Swarm Optimization for Wireless Sensor Network Location Problem