An Improved DV-Hop Scheme Based on Path Matching and Particle Swarm Optimization Algorithm

  • Qinqin Shi
  • Qiang Xu
  • Jianping Zhang


Distance vector hop (DV-Hop) is a frequently-used localization technology for wireless sensor networks. The traditional DV-Hop scheme estimates the node–anchor distance depending on the hop-count between the network nodes. It is the advantage of the scheme because no costive direct range finding is needed, but it still is the disadvantage of the scheme because the heterogeneity of network topology will make the node–anchor distance estimation precision poor and the localization precision unstable. Since the heterogeneity of network topology is very common due to random node deployment in real applications, the effectiveness of DV-Hop scheme in these applications becomes difficult to confirm and the algorithm needs applicability improvement. Focusing on above problem of the traditional DV-Hop, improved strategies are provided. A path matching algorithm is presented to find out the optimal anchor-anchor shortest path, which is used to determine the average hop distance between an unknown node and its target anchor independently, aiming at making the estimated node-anchor distance as close as possible to the real distance; furtherly, a modified particle swarm optimization algorithm is presented to optimize the initial position of each unknown node, aiming at improving the whole node localization accuracy of the network. Simulations are carried out on different network topologies both in square area and in C-shaped area, and comparisons are made for our scheme with the traditional DV-Hop and the other three existed representative improved schemes. Results show that our scheme has better performance both on distance estimation accuracy and on average node localization accuracy.


DV-Hop Node localization Path matching Trilateration Particle swarm optimization algorithm 



This work was financially supported by National Nature Science Foundation of China (No. 61103180) and The Collaborative Innovation Foundation of Shanghai Institute of Technology (No. XTCX2018-15).


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Authors and Affiliations

  1. 1.School of Computer Science and Information EngineeringShanghai Institute of TechnologyShanghaiChina
  2. 2.Suzhou Zhongke Advanced Technology Research Institute Co., Ltd.SuzhouChina
  3. 3.Sino Parking Tech Co., Ltd.ShanghaiChina

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