Skip to main content
SpringerLink
Log in

Novel Positioning Service Computing Method for WSN

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

The challenge of wireless sensor network (WSN) becomes truly pervasive is that of reliable positioning problem. The positioning accuracy of the traditional DV-HOP (Distance Vector-HOP) algorithm has very strong dependence for density of anchor node, only when anchor node density reaches a certain extent, will it has better positioning effect. Therefore, it increases the cost of network service. In this paper, we propose novel positioning service computing method for WSN. The method can estimate distance of nodes which has same neighbor nodes by maximum likelihood estimation. It effectively improves the accuracy of measuring distance among nodes. The nodes can obtain itself average hop distance by the distance from itself to its circular nodes and the number of jump. It’s a good solution to solve the dependence of traditional DV-HOP algorithm on anchor node density. In the positioning service stage, based on intersection density among circles with anchor node as center and estimation distance as radius, the method can replace triangle positioning algorithm by the method of estimating the node coordinates to be measured. The belief degree of reliable positioning service can be computed by our proposed fusion method. Our experiments show that our presented method can solve the problem of estimated error of distance caused by loop and it can greatly improve the efficiency of positioning service.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14

Similar content being viewed by others

References

  1. Zhang, D. G., & Li, G. (2014). An energy-balanced routing approach based on forward-aware factor for wireless sensor network. IEEE Transactions on Industrial Informatics, 10(1), 766–773.

    Article  Google Scholar 

  2. Zhang, D. G., & Zhao, C. P. (2012). A new medium access control protocol based on perceived data reliability and spatial correlation in wireless sensor network. Computers & Electrical Engineering, 38(3), 694–702.

    Article  MathSciNet  Google Scholar 

  3. Niculescu, D. (2001). Ad hoc positioning system (APS). In Global Telecommunications Conference. GLOBECOM’01 (Vol. 5(1), pp. 30–38). IEEE.

  4. Niculescu, D., & Nath, B. (2003). DV based positioning in ad hoc networks. Telecommunication Systems, 22(1–4), 267–280.

    Article  Google Scholar 

  5. Zhang, D. G. (2012). A new approach and system for attentive mobile learning based on seamless migration. Applied Intelligence, 36(1), 75–89.

    Article  Google Scholar 

  6. Shang, Y., & Ruml, W. (2004). Improved MDS-based localization. In INFOCOM 2004 (Vol. 4, pp. 2640–2651). IEEE.

  7. Wang, Z. (2009). Improvement on APIT localization algorithms for wireless sensor networks. In International conference on networks security, wireless communications and trusted computing (Vol. 1(1), pp. 40–48). IEEE.

  8. Wang, Y., Wang, X., Wang, D., et al. (2009). Range-free localization using expected hop progress in wireless sensor networks. IEEE Transactions on Parallel and Distributed Systems, 20(10), 1540–1552.

    Article  Google Scholar 

  9. Huang, B. Q. (2012). Estimating distances via connectivity in wireless sensor networks. International Conference on WCMC, 1(1), 50–59.

    Google Scholar 

  10. Zhang, D. G., & Zhu, Y. N. (2012). A new constructing approach for a weighted topology of wireless sensor networks based on local-world theory for the Internet of Things (IOT). Computers & Mathematics with Applications, 64(5), 1044–1055.

    Article  Google Scholar 

  11. Zhang, D. G., Wang, X., & Song, X. D. (2015). New clustering routing method based on PECE for WSN. EURASIP Journal on Wireless Communications and Networking, 2015(162), 1–13. doi:10.1186/s13638-015-0399-x.

    Google Scholar 

  12. Meng, W., Xiao, W., & Xie, L. (2011). An efficient EM algorithm for energy-based multi-source localization in wireless sensor networks. IEEE Transactions on Instrumentation and Measurement, 60(3), 1017–1027.

    Article  Google Scholar 

  13. Zhang, D. G., & Zhang, X. D. (2012). Design and implementation of embedded un-interruptible power supply system (EUPSS) for web-based mobile application. Enterprise Information Systems, 6(4), 473–489.

    Article  Google Scholar 

  14. Zhang, D. G., & Liang, Y. P. (2013). A kind of novel method of service-aware computing for uncertain mobile applications. Mathematical and Computer Modelling, 57(3–4), 344–356.

    Article  Google Scholar 

  15. Massimo, F. (2007). Random networks for communication: from statistical physics to information systems (pp. 20–70). Cambridge: Cambridge University Press.

    Google Scholar 

  16. Zhang, D. G., & Kang, X. J. (2012). A novel image de-noising method based on spherical coordinates system. EURASIP Journal on Advances in Signal Processing, 1, 110. doi:10.1186/1687-6180-2012-110.

    Article  Google Scholar 

  17. Stanislava, S. (2009). Cluster head election techniques for coverage preservation in wireless sensor networks. Ad Hoc Networks, 5(7), 955–972.

    Google Scholar 

  18. Samaras, I. K., & Hassapis, G. D. (2013). A modified DPWS protocol stack for 6LoWPAN-based wireless sensor networks. IEEE Transactions on Industrial Informatics, 9(1), 209–217.

    Article  Google Scholar 

  19. Zhang, D. G., Zheng, K., & Zhang, T. (2014). A novel multicast routing method with minimum transmission for WSN of cloud computing service. Soft Computing, 19(7), 1817–1827.

    Article  Google Scholar 

  20. Fisher, J. (1999). Fast JPDA multi-target tracking. Applied Optics, 28(1), 371–375.

    Google Scholar 

  21. Zhang, D. G., Xu, G. Y., & Shi, Y. C. (2004) Extended method of evidence theory for pervasive computing. Chinese Journal of Computer (in Chinese).

  22. Saha, F. T., & Chang, T. C. (2007). An efficient algorithm for multi-sensor track fusion. IEEE Transactions on Aero-space Electronic Systems, 34(1), 200–210.

    Article  Google Scholar 

  23. Reid, D. B. (1999). An algorithm for tracking multiple targets. IEEE Transaction on Automatic Control, 24(6), 843–854.

    Article  Google Scholar 

  24. Mori, S., Chong, C. Y., & Wishner, R. P. (1998). Tracking and classifying multiple targets without a priori identification. IEEE Transaction on Automatic Control, AC-31(5), 401–409.

    Article  MATH  Google Scholar 

  25. Musick, S., Kastella, K., & Mahler, K. (2005). A practical implementation of joint multi-target probabilities. SPIE Proceedings, 3374, 26–37.

    Article  Google Scholar 

  26. Zhang, D. G. (2015). Extended AODV routing method based on distributed minimum transmission (DMT) for WSN. International Journal of Electronics and Communications, 69(1), 371–381.

    Article  Google Scholar 

  27. Nan, W., Liu, F., & Wang, S. (2015). Algorithm for locating nodes in WSN based on modifying hops and hopping distances. Microelectronics & Computer [J], 32(01), 91–95.

    Google Scholar 

  28. Xia, S., Zou, J., Zhu, X., et al. (2015). Improvement on DV-Hop localization algorithm in wireless sensor networks. Journal of Computer Applications, 35(2), 340–344.

    Google Scholar 

  29. Zhang, D. G., Wang, X., & Song, X. D. (2014). A novel approach to mapped correlation of ID for RFID anti-collision. IEEE Transactions on Services Computing, 7(4), 741–748.

    Article  Google Scholar 

  30. Zhang, D. G., & Song, X. D. (2015). New agent-based proactive migration method and system for big data environment (BDE). Engineering Computations, 32(8), 2443–2466.

    Article  Google Scholar 

  31. Zhang, D. G., Zheng, K., & Zhao, D. X. (2016). Novel quick start (QS) method for optimization of TCP. Wireless Networks, 22(1), 211–222.

    Article  Google Scholar 

  32. Zhang, D. G., Li, G., & Pan, Z. H. (2014). A new anti-collision algorithm for RFID tag. International Journal of Communication Systems, 27(11), 3312–3322.

    Google Scholar 

Download references

Acknowledgments

This research work is supported by National Natural Science Foundation of China (Grant No. 61571328), Major projects of science and technology in Tianjin (No. 15ZXDSGX00050), Training plan of Tianjin University Innovation Team (No. TD12-5016), Major projects of science and technology for their services in Tianjin (No. 16ZXFWGX00010), Training plan of Tianjin 131 Innovation Talent Team (No. TD2015-23).

Author information

Authors and Affiliations

  1. Key Laboratory of Computer Vision and System, Tianjin University of Technology, Ministry of Education, Tianjin, 300384, China

    De-gan Zhang

  2. Tianjin Key Lab of Intelligent Computing and Novel Software Technology, Tianjin University of Technology, Tianjin, 300384, China

    De-gan Zhang, Hong-li Niu, Si Liu & Xue-chao Ming

  3. School of Electronic and Information Engineering, University of Sydney, Sydney, NSW, 2006, Australia

    De-gan Zhang

Authors
  1. De-gan Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Hong-li Niu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Si Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Xue-chao Ming
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Si Liu.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhang, Dg., Niu, Hl., Liu, S. et al. Novel Positioning Service Computing Method for WSN. Wireless Pers Commun 92, 1747–1769 (2017). https://doi.org/10.1007/s11277-016-3632-y

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-016-3632-y

Keywords

Search

Navigation