Research On DV-Hop Algorithm Based On Priority Node Localization And Artificial Fish Swarm Algotithm Optimization

Wireless Sensor Network(Wireless Sensor Network, WSN) has the capacities of self-organizing, widely-distributing, which determine its popularity. Wireless Sensor Network is initially applied in the military field, and then is introduced to the civilian areas, where it helps to reinforce people’s ability of information-searching. Positioning technology is one of the key technologies of Wireless Sensor Network. At present, two widely-accepted positioning technologies are: positioning technology based on distance measuring and positioning technology based on the range.In this paper, the DV-Hop algorithm, based on the range positioning technology is the most concerned part. DV-Hop algorithm is low-costing, simply-calculating which helps to gain its popularity. However, this algorithm also has its own deficiency of inaccuracy. To cope with which problem, this paper comes up with the improvement by using priority node localization and artificial fish algorithm. The DV-Hop algorithm is going to be improved from the following three aspects.(1) Priority node location. This paper will refine the communication radius of anchor node, has 3 communication radius: R/3, 2R/3 and R. In accordance with the correlation between the hop and communication radius, we will firstly calculates the distance between the unknown node and anchor node, within the limit of the anchor node communication radius R. Then, those which meet the standard distance will be firstly node localized; while those which fail to meet the standard distance will be localized subsequently. The method of refining anchor nod communication radius into three radiuses can reduce not only the risk of miscalculation of the hop, but also the risk of the location miscalculation of some unknown nodes.(2) The average hopping distance. This paper will use the method of weighted assignment to modify the average hopping distance. The average jumping distance cannot represent the real distance. To this inefficiency, this paper adopts the weighted method to get the weighted coefficient, and then assigns different weight to each anchor node, and at the same time, selects the most short-distant unknown nodes as the referential anchor nodes. Through the modification of the average hopping distance, we will be able to get the more precise hopping distance.(3) The unknown node coordinates. With the improved artificial fish algorithm, this paper will modify the unknown node coordinates. To the low accuracy of positioning calculation node coordinates, this paper uses the artificial fish algorithm to optimize the localization, improve the artificial fish algorithm as well. The artificial fish algorithm will be segmented, the artificial fish in low food concentration will be eliminated, and the convergence rate will be improved; meanwhile, the parameters of artificial fish will be dynamically modified, and the random behavior will be modified as well, in preventing of artificial fish’s blind random behavior. Based on the improved artificial fish algorithm, the convergence rate will be speeded up, which will be useful to find the optimal solution globally and improve the positioning accuracy.Finally,this paper use Matlab to simulate the improved algorithm by comparing with the original DV-Hop algorithm,and then verify the feasibility of the improved algorithm and analyze the simulation results.Through simulation,the improved algorithm is proved to better off the original DV-Hop algorithm in localization accuracy and stability.