Abstract: DV_hop algorithm is one of the classical range-free sensor node location algorithms. However, due to the uneven distribution of nodes, the distance between the unknown nodes and the anchor nodes calculated by the average hop distance is far from the actual distance, resulting in the lack of positioning accuracy. To solve this problem, an improved DV_Hop algorithm based on improved wolf colony algorithm (IWCA) is proposed by virtue of the fact that wolf colony algorithm needs less calculation parameters and has good optimization accuracy. Firstly, the estimated distance of DV_hop algorithm is optimized. For the unknown node with 1 hop from anchor nodes, the distance between itself and anchor nodes is directly calculated by RSSI method, so as to reduce the error of estimated distance. Secondly, because the wolf colony algorithm is easy to fall into the local optimum, an improved wolf colony algorithm (IWCA) is proposed. The idea of simulated annealing is adopted. When the position of N iterations of probe wolf is not changed, it is allowed to swim in the direction of poor effect with a certain probability. The way of swimming is chaos mapping. Finally, The IWCA is applied to the calculation of node location, so as to reduce the error of DV_Hop algorithm when calculating node location. Theoretical analysis and simulation experiments show that compared with similar algorithms, IWCADV_Hop can improve the accuracy of sensor network node location.

Key words: wireless sensor network, node location, DV_Hop, wolf colony algorithm