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Improved algorithm for distributed localization in wireless sensor networks

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Abstract

Many sensor network applications require location awareness, but it is often too expensive to equip a global positioning system (GPS) receiver for each network node. Hence, localization schemes for sensor networks typically use a small number of seed nodes that know their locations and protocols whereby other nodes estimate their locations from the messages they receive. For the inherent shortcomings of general particle filter (the sequential Monte Carlo method) this paper introduces particle swarm optimization and weighted centroid algorithm to optimize it. Based on improvement a distributed localization algorithm named WC-IPF (weighted centroid algorithm improved particle filter) has been proposed for localization. In this localization scheme the initial estimate position can be acquired by weighted centroid algorithm. Then the accurate position can be gotten via improved particle filter recursively. The extend simulation results show that the proposed algorithm is efficient for most condition.

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References

  1. Ko Y, Nitin H V. Location aided routing (LAR) in mobile Ad-hoc networks [J]. Wireless Networks, 2000, 6(9): 307–321.

    Article  MATH  Google Scholar 

  2. Li Li, Dong Shu-song, Wen Xiang-ming. An energy efficient clustering routing algorithm for wireless sensor networks [J]. Journal of China Universities of Posts and Telecommunications, 2006, 13(3): 71–75 (in Chinese).

    Article  MATH  Google Scholar 

  3. Guo Shu-jie, Zheng Jie, Qu Yu-gui, et al. Clustering and multi-hop routing with power control in wireless sensor networks [J]. Journal of China Universities of Posts and Telecommunications, 2007, 14(1): 49–57 (in Chinese).

    Article  Google Scholar 

  4. Patwari N, Ash J N, Kyperountas S, et al. Locating the nodes: Cooperative localization in wireless sensor networks [J]. IEEE Signal Processing Magazine, 2005, 22(4): 54–69.

    Article  Google Scholar 

  5. Patwari N, Hero A O, Perkins M, et al. Relative location estimation in wireless sensor networks [J]. IEEE Transactions on Signal Processing, 2003, 51(8): 2137–2148.

    Article  Google Scholar 

  6. Doherty L, Pister K S J, Ghaoui L E. Convex position estimation in wireless sensor networks [C]// Proceedings of 20th Annual Joint Conference of the IEEE Computer and Communications Societies. Piscataway, NJ, USA: IEEE, 2001: 1655–1663.

    Google Scholar 

  7. Shang Y, Ruml W. Improved MDS-based localization [C]// Proceedings of 23rd Annual Joint Conference of the IEEE Computer and Communications Societies. Piscataway, NJ, USA: IEEE, 2004: 2640–2651.

    Google Scholar 

  8. Nirupama B, John H, Deborah E. GPS-less low cost outdoor localization for very small devices [J]. IEEE Personal Communications Magazine, 2000, 7(5): 28–34.

    Article  Google Scholar 

  9. Bergamo P, Mazzini G. Localization in sensor networks with fading and mobility [C]// Proceedings of IEEE International Symposium on Personal, Indoor and Mobile Radio Communications. Piscataway, NJ, USA: IEEE, 2002: 750–754.

    Google Scholar 

  10. Su Kuo-feng, Ou C H, Jiau H C. Localization with mobile anchor points in wireless sensor networks [J]. IEEE Transactions on Vehicular Technology, 2005, 54(3): 1187–1197.

    Article  Google Scholar 

  11. Hu L, Evans D. Localization for mobile sensor networks [C]// Proceedings of 10th Annual International Conference on Mobile Computing and Networking. NY, USA: ACM, 2004: 45–47.

    Chapter  Google Scholar 

  12. Camp T, Boleng J, Davies V. A survey of mobility models for Ad Hoc networks research [J]. Wireless Communications and Mobile Computing, 2002, 2(5): 483–502.

    Article  Google Scholar 

  13. Kennedy J, Eberhart R C. Particle swarm optimization [C]// Proceedings of IEEE International Conference on Neural Networks. Piscataway, NJ: IEEE, 1995: 1942–1948.

    Chapter  Google Scholar 

  14. Krohling R A. Gaussian swarm: A novel particle swarm optimization algorithm [C]// Proceedings of the IEEE Conference on Cybernetics and Intelligent Systems (CIS). Singapore: IEEE, 2004: 372–376.

    Google Scholar 

  15. Lee J, Cho K, Lee S, et al. Distributed and energy-efficient target localization and tracking in wireless sensor networks [J]. Elsevier Computer Communications, 2006, 29(13–14): 2494–2505.

    Google Scholar 

Download references

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Authors and Affiliations

  1. Department of Electronic Engineering, Shanghai Jiaotong University, Shanghai, 200240, China

    You-ping Zhong  (钟幼平), Xing-hong Kuang  (匡兴红) & Pei-wei Huang  (黄佩伟)

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  1. You-ping Zhong  (钟幼平)
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  2. Xing-hong Kuang  (匡兴红)
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  3. Pei-wei Huang  (黄佩伟)
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Correspondence to You-ping Zhong  (钟幼平).

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Zhong, Yp., Kuang, Xh. & Huang, Pw. Improved algorithm for distributed localization in wireless sensor networks. J. Shanghai Jiaotong Univ. (Sci.) 15, 64–69 (2010). https://doi.org/10.1007/s12204-010-8112-z

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  • DOI: https://doi.org/10.1007/s12204-010-8112-z

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