An Improved Localization Algorithm Based on DV-Hop

  • Liquan ZhaoEmail author
  • Kexin Zhang
  • Yanfei Jia
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1084)


In wireless sensor network’s localization, the distances vector per hop algorithm is typical localization, to improve the location error, an improved localization algorithm is proposed based on the distances vector per hop algorithm. Firstly, we set the different communication distances for different nodes. Each communication distance corresponds to one hop. Secondly, if the hop count is less than one, the average hop distance of the nearest anchor node is used as the hop distance of unknown node. On the contrary, the weighted average hop distance sum of the nearest four anchor nodes is used as the hop distance of unknown node. In the simulations, we compare the proposed algorithm with distances vector per hop algorithm and weighted-based distances vector per hop algorithm. The simulation results of matlab showed that the proposed method has smaller error for unknown node’s localization than the other algorithm.


Wireless sensor networks Localization error Distances vector per hop algorithm Hop count 


  1. 1.
    Liao, W.H., Shih, K.P., Lee, Y.C.: A localization protocol with adaptive power control in wireless sensor networks. Comput. Commun. 31(10), 2496–2504 (2008)CrossRefGoogle Scholar
  2. 2.
    Zhao, X., Zhou, Y.: Development and application of on-line monitoring and fault diagnosis system for centrifugal PUMP based on lab VIEW. J. Northeast Electr. Pow. Univ. 37(2), 66–72 (2017)Google Scholar
  3. 3.
    Zhu, H., Li, Y.: Distribution transformer monitoring system operating parameters and design. J. Northeast Electr. Pow. Univ. 38(5), 74–79 (2018)Google Scholar
  4. 4.
    Mehaseb, M.A., Gadallah, Y., El-Hennawy, H.: WSN application traffic characterization for integration within the Internet of Things. In: Proceedings of IEEE International Conference on Mobile Ad-hoc and Sensor Networks, Dalian, pp. 318–323 (2013)Google Scholar
  5. 5.
    Kouche, A.E., Al-Awami, L., Hassanein, H., Obaia, K.: WSN application in the harsh industrial environment of the oil sands. In: Proceedings of International Wireless Communication and Mobile Computing Conference, Istanbul, Turkey, pp. 613–618 (2011)Google Scholar
  6. 6.
    Niclescu, D., America, N.L.: Communication paradigms for sensor network. IEEE Commun. Mag. 43(3), 116–122 (2005)CrossRefGoogle Scholar
  7. 7.
    Guo, X., Sun, M.: Design of communication manager for hydropower station. J. Northeast Electr. Pow. Univ. 37(4), 94–97 (2017)Google Scholar
  8. 8.
    Jin, E., Jin, Y., Chen, Y., Zhao, Y.: Study on the new integrated protection of intelligent substations. J. Northeast Dianli Univ. 36(6), 25–29 (2016)Google Scholar
  9. 9.
    Chatterjee, A.: A fletcher-reeves conjugate neural-network-based localization algorithm for wireless sensor networks. IEEE Trans. Veh. Technol. 59(2), 823–830 (2010)CrossRefGoogle Scholar
  10. 10.
    Li, M., Liu, Y.: Range-free localization in an isotropic sensor networks with holes. IEEE/ACM Trans. Network. 18(1), 320–332 (2010)CrossRefGoogle Scholar
  11. 11.
    Kwon, O., Song, H., Park, S.: The effects of stitching orders in patch-and-stitch WSN localization algorithms. IEEE Trans. Parallel Distrib. Syst. 20(9), 1380–1391 (2009)CrossRefGoogle Scholar
  12. 12.
    Katenka, N., Levina, E., Michailidis, G.: Robust target localization from binary decisions in wireless sensor networks. Technometrics 448–461 (2008)Google Scholar
  13. 13.
    Han, G., Xu, H., Duong, T.Q., et al.: Localization algorithms of wireless sensor networks: a survey. Telecommun. Syst. 2419–2436 (2013)Google Scholar
  14. 14.
    Grewal, M.S., Weill, L.R., Andrews, A.P.: Global Positioning Systems, Inertial Navigation And Integration. Wiley, Hoboken (2007)CrossRefGoogle Scholar
  15. 15.
    Zengyou, S., Chi, Z.: Adaptive clustering algorithm in WSN based on energy and distance. J. Northeast Dianli Univ. 36(1), 82–86 (2016)Google Scholar
  16. 16.
    Teng, Z., Xu, M., Li, Z.: Nodes deployment in wireless sensor networks based on improved reliability virtual force algorithm. J. Northeast Dianli Univ. 36(2), 86–89 (2016)Google Scholar
  17. 17.
    Niculescu, D., Nath, B.: Ad-hoc positioning system (APS). In: Proceedings of the 2001 IEEE Global Telecommunications Conference [S1], pp. 2926–2931. IEEE Communication Society (2001)Google Scholar
  18. 18.
    Niculescu, D., Nath, B.: DV based positioning in ad hoc networks. J. Telecommun. Syst. 22(4), 267–280 (2003)CrossRefGoogle Scholar
  19. 19.
    Yi, X., Liu, Y., Deng, L., He, Y.: An improved DV-hop positioning algorithm with modified distance error for wireless sensor network. In: The 2nd International Symposium on Knowledge Acquisition and Modeling, vol. 2, pp. 216–218 (2009)Google Scholar
  20. 20.
    Hu, Y., Li, X.: An improvement of DV-Hop localization algorithm for wireless sensor networks. Telecommun. Syst. 13–18 (2013)Google Scholar
  21. 21.
    Singh, S.P., Sharma, S.C.: A PSO based improved localization algorithm for wireless sensor network. Wireless Pers. Commun. 1–17 (2017)Google Scholar
  22. 22.
    Tianxiao, C., Xiaolong, Z., Wenhao, L.: Gear fault diagnosis based on hilbert envelope spectrum and SVM. J. Northeast Elect. Power Univ. 37(6), 56–61 (2017)Google Scholar

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© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Key Laboratory of Modern Power System Simulation and Control & Renewable Energy TechnologyMinistry of Education (Northeast Electric Power University)JilinChina
  2. 2.College of Electrical and Information EngineeringBeihua UniversityJilinChina

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