Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
Skip to main content
Springer Nature Link
Log in

Pascal’s triangle-based range-free localization for anisotropic wireless networks

  • Published:
Wireless Networks Aims and scope Submit manuscript

Abstract

This paper introduces a Pascal’s triangle model to draw the potential locations and their probabilities for a normal node given the hop counts to the anchors according to the extent of detour of the shortest paths. Based on our proposed model, a Pascal’s triangle-based localization (PTL) algorithm using local connectivity information is presented for anisotropic wireless networks with a small number of anchors. The superiority of the PTL algorithm has been validated over the state-of-the-art algorithms through MATLAB simulations. We have shown that compared to the other algorithms, the PTL algorithm achieves higher localization accuracy with even fewer anchors. We have also validated the performance of the PTL algorithm in a real environment.

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

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

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
Fig. 15
Fig. 16
Fig. 17
Fig. 18

Similar content being viewed by others

Notes

  1. The shortest paths to an anchor pair from a normal node is referred to as the compound shortest path. We give the exact definition of the compound shortest path in Sect. 5.2.

  2. A \((1-\alpha )\) confidence interval for the true mean \(\mu\) is defined as \(\mu \in (\bar{\mu }- z_{\alpha /2}\frac{\bar{\sigma }}{\sqrt{S}}, \bar{\mu } + z_{\alpha /2}\frac{\bar{\sigma }}{\sqrt{S}})\) with sample mean \(\bar{\mu }\), sample standard deviation \(\bar{\sigma }\), sample size S, and z-score \(z_{\alpha /2}\).

References

  1. Boukerche, A., Oliveira, H. A. B. F., Nakamura, E. F., & Loureiro, A. A. F. (2008). Vehicular ad hoc networks: A new challenge for localization-based systems. Computer Communications, 31(12), 2838–2849.

    Article  Google Scholar 

  2. Chong, C.-Y., & Kumar, S. P. (2003). Sensor networks: Evolution, opportunities, and challenges. Proceedings of the IEEE, 91(8), 1247–1256.

    Article  Google Scholar 

  3. Lee, S., & Lee, C. (2011). Broadcasting in mobile ad hoc networks. In X. Wang (Ed.), Mobile ad-hoc networks: Protocol design (pp. 579–594). Winchester: InTech.

    Google Scholar 

  4. Boukerche, A. (2008). Algorithms and protocols for wireless sensor networks. Hoboken: Wiley.

    Book  Google Scholar 

  5. Mostefaoui, A., Melkemi, M., & Boukerche, A. (2014). Localized routing approach to bypass holes in wireless sensor networks. IEEE Transactions on Computers, 63(12), 3053–3065.

    Article  MathSciNet  Google Scholar 

  6. Chitte, S. D., Dasgupta, S., & Ding, Z. (2009). Distance estimation from received signal strength under log-normal shadowing: Bias and variance. IEEE Signal Processing Letters, 16(3), 216–218.

    Article  Google Scholar 

  7. Jeon, N.-R., Lee, H.-B., Park, C. G., Cho, S. Y., & Kim, S.-C. (2010). Superresolution TOA estimation with computational load reduction. IEEE Transactions on Vehicular Technology, 59(8), 4139–4144.

    Article  Google Scholar 

  8. Gholami, M. R., Gezici, S., & Ström, E. G. (2013). A concave-convex procedure for TDOA based positioning. IEEE Communications Letters, 17(4), 765–768.

    Article  Google Scholar 

  9. Shen, Y., & Win, M. Z. (2010). On the accuracy of localization systems using wideband antenna arrays. IEEE Transactions on Communications, 58(1), 270–280.

    Article  Google Scholar 

  10. Boukerche, A., Oliveira, H. A. B. F., Nakamura, E. F., & Loureiro, A. A. F. (2007). Localization systems for wireless sensor networks. IEEE Wireless Communications, 14(6), 6–12.

    Article  Google Scholar 

  11. Oliveira, H. A. B. F., Boukerche, A., Nakamura, E. F., & Loureiro, A. A. F. (2009). An efficient directed localization recursion protocol for wireless sensor networks. IEEE Transactions on Computers, 58(5), 677–691.

    Article  MathSciNet  Google Scholar 

  12. Oliveira, H. A. B. F., Boukerche, A., Nakamura, E. F., & Loureiro, A. A. F. (2009). Localization in time and space for wireless sensor networks: An efficient and lightweight algorithm. Performance Evaluation, 66(3–5), 209–222.

    Article  Google Scholar 

  13. Gribben, J., & Boukerche, A. (2014). Location error estimation in wireless ad hoc networks. Ad Hoc Networks, 13(Part B), 504–515.

    Article  Google Scholar 

  14. Kovár, P., Kacmarik, P., & Vejrazka, F. (2011). Interoperable GPS, GLONASS and Galileo software receiver. IEEE Aerospace and Electronic Systems Magazine, 26(4), 24–30.

    Article  Google Scholar 

  15. Niculescu, D. & Nath, B. (2001). Ad hoc positioning system (APS). In Proceedings of the IEEE GLOBECOM (Vol. 5, pp. 2926–2931).

  16. Shang, Y., Ruml, W., Zhang, Y. & Fromherz, M. P. J. (2003). Localization from mere connectivity. In Proceedings of the ACM MobiHoc (pp. 201–212).

  17. Xiao, Q., Xiao, B., Cao, J., & Wang, J. (2010). Multihop range-free localization in anisotropic wireless sensor networks: A pattern-driven scheme. IEEE Transactions on Mobile Computing, 9(11), 1592–1607.

    Article  Google Scholar 

  18. Wang, Y., Wang, X., Wang, D., & Agrawal, D. P. (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 

  19. Zhao, J., Xi, W., He, Y., Liu, Y., Li, X.-Y., Mo, L., et al. (2013). Localization of wireless sensor networks in the wild: Pursuit of ranging quality. IEEE/ACM Transactions on Networking, 21(1), 311–323.

    Article  Google Scholar 

  20. Wu, G., Wang, S., Wang, B., Dong, Y., & Yan, S. (2012). A novel range-free localization based on regulated neighborhood distance for wireless ad hoc and sensor networks. Computer Networks, 56(16), 3581–3593.

    Article  Google Scholar 

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

  22. Shang, Y., Rumi, W., Zhang, Y., & Fromherz, M. (2004). Localization from connectivity in sensor networks. IEEE Transactions on Parallel and Distributed Systems, 15(11), 961–974.

    Article  Google Scholar 

  23. Ji, X. & Zha, H. (2004). Sensor positioning in wireless ad-hoc sensor networks using multidimensional scaling. In Proceedings of the IEEE INFOCOM (Vol. 4, pp. 2652–2661).

  24. Li, M., & Liu, Y. (2010). Rendered path: Range-free localization in anisotropic sensor networks with holes. IEEE/ACM Transactions on Networking, 18(1), 320–332.

    Article  Google Scholar 

  25. El Assaf, A., Zaidi, S., Affes, S. & Kandil, N. (2014). Range-free localization algorithm for heterogeneous wireless sensor networks. In Proceedings of the IEEE WCNC (pp. 2805–2810).

  26. Xiao, B., Chen, L., Xiao, Q., & Li, M. (2009). Reliable anchor-based sensor localization in irregular areas. IEEE Transactions on Mobile Computing, 9(1), 60–72.

    Article  Google Scholar 

  27. Zhang, S., Liu, X., Wang, J., Cao, J., & Min, G. (2015). Accurate range-free localization for anisotropic wireless sensor networks. ACM Transactions on Sensor Networks, 11(3), 51.

    Article  Google Scholar 

  28. Liu, X., Zhang, S., Wang, J., Cao, J. & Xiao, B. (2011). Anchor supervised distance estimation in anisotropic wireless sensor networks. In Proceedings of the IEEE WCNC (pp. 938–943).

  29. Woo, H., Lee, C. & Oh, S. (2013). Reliable anchor node based range-free localization algorithm in anisotropic wireless sensor networks. In Proceedings of the IEEE ICOIN (pp. 618–622).

  30. El Assaf, A., Zaidi, S., Affes, S. & Kandil, N. (2013). Efficient range-free localization algorithm for randomly distributed wireless sensor networks. In Proceedings of the IEEE GLOBECOM (pp. 201–206).

  31. Torgerson, W. S. (1965). Multidimensional scaling of similarity. Psychometrika, 30(4), 379–393.

    Article  Google Scholar 

  32. Lee, S., Lee, D., & Lee, C. (2011). Enhanced DV-Hop algorithm with reduced hop-size error in ad hoc networks. IEICE Transactions on Communications, E94–B(7), 2130–2132.

    Article  Google Scholar 

  33. Woo, H., Lee, S. & Lee, C. (2013). Range-free localization with isotropic distance scaling in wireless sensor networks. In Proceedings of the IEEE ICOIN (pp. 632–636).

  34. Lee, S., Woo, H., & Lee, C. (2012). Wireless sensor network localization with connectivity-based refinement using mass spring and Kalman filtering. EURASIP Journal on Wireless Communications and Networking. doi:10.1186/1687-1499-2012-152.

  35. Yang, C., Zhu, W., Wang, W., Chen, L., Chen, D. & Cao, J. (2014). Connectivity-based virtual potential field localization in wireless sensor networks. In Proceedings of the IEEE WCNC (pp. 2641–2646).

  36. Sheu, J.-P., Chen, P.-C., & Hsu, C.-S. (2008). A distributed localization scheme for wireless sensor networks with improved grid-scan and vector-based refinement. IEEE Transactions on Mobile Computing, 7(9), 1110–1123.

    Article  Google Scholar 

  37. Lim, H. & Hou, J. C. (2005). Localization for anisotropic sensor networks. In Proceedings of the IEEE INFOCOM (Vol. 1, pp. 138–149).

  38. Lee, J., Chung, W., & Kim, E. (2011). A new range-free localization method using quadratic programming. Computer Communications, 34(8), 998–1010.

    Article  Google Scholar 

  39. Lee, J., Choi, B., & Kim, E. (2013). Novel range-free localization based on multidimensional support vector regression trained in the primal space. IEEE Transactions on Neural Networks and Learning Systems, 24(7), 1099–1113.

    Article  Google Scholar 

  40. Zhang, S., Tan, G., Jiang, H., Li, B., & Wang, C. (2014). On the utility of concave nodes in geometric processing of large-scale sensor networks. IEEE Transactions on Wireless Communications, 13(1), 132–143.

    Article  Google Scholar 

  41. Wang, Y., Gao, J. & Mitchell, J. S. B. (2006). Boundary recognition in sensor networks by topological methods. In Proceedings of the ACM MobiCom (pp. 122–133).

  42. Lee, S., Park, C., Lee, M.-J., & Kim, S. (2014). Multihop range-free localization with approximate shortest path in anisotropic wireless sensor networks. EURASIP Journal on Wireless Communications and Networking. doi:10.1186/1687-1499-2014-80.

  43. Boukerche, A., Oliveira, H. A. B. F., Nakamura, E. F., & Loureiro, A. A. F. (2009). DV-Loc: A scalable localization protocol using Voronoi diagrams for wireless sensor networks. IEEE Wireless Communications, 16(2), 50–55.

    Article  Google Scholar 

  44. Kim, S., & Lee, B.-T. (2009). Scalable DV-Hop localization algorithm with constrained multilateration for wireless sensor network. IEICE Transactions on Communications, E92–B(10), 3075–3078.

    Article  Google Scholar 

  45. Zhong, Z., & He, T. (2011). RSD: A metric for achieving range-free localization beyond connectivity. IEEE Transactions on Parallel and Distributed Systems, 22(11), 1943–1951.

    Article  MathSciNet  Google Scholar 

  46. Chan, Y. W. E., & Soong, B. H. (2011). A new lower bound on range-free localization algorithms in wireless sensor networks. IEEE Communications Letters, 15(1), 16–18.

    Article  Google Scholar 

  47. Karbasi, A., & Oh, S. (2013). Robust localization from incomplete local information. IEEE/ACM Transactions on Networking, 21(4), 1131–1144.

    Article  Google Scholar 

  48. Gao, D., Chen, P., Foh, C. H., & Niu, Y. (2011). Hop-distance relationship analysis with quasi-UDG model for node localization in wireless sensor networks. EURASIP Journal on Wireless Communications and Networking. doi:10.1186/1687-1499-2011-99.

  49. Gubner, J. A. (2006). Probability and random processes for electrical and computer engineers. Cambridge: Cambridge University Press.

    Book  MATH  Google Scholar 

  50. Wang, X. (2006). QoS issues and QoS constrained design of wireless sensor networks. Ph.D. dissertation, University of Cincinnati.

  51. Lee, S., Koo, B., Jin, M., Park, C., Lee, M.-J. & Kim, S. (2014). Range-free indoor positioning system using smartphone with Bluetooth capability. In Proceedings of the IEEE/ION PLANS (pp. 657–662).

  52. Hsu, A. C.-C., Wei, D. S. L., & Kuo, C.-C. J. (2015). Coexistence Wi-Fi MAC design for mitigating interference caused by collocated Bluetooth. IEEE Transactions Computers, 64(2), 341–352.

    MathSciNet  Google Scholar 

Download references

Acknowledgments

This work has been supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (NRF-2013R1A1A2062728) and the ICT R&D program of MSIP/IITP (14-044, Technology Development of GNSS Interference Verification Platform).

Author information

Authors and Affiliations

  1. Department of Electronics and Computer Engineering, Hanyang University, Seoul, Korea

    Sangwoo Lee, Myungjun Jin, Bonhyun Koo & Sunwoo Kim

  2. Department of Satellite Wireless Convergence Research, Electronics and Telecommunications Research Institute, Daejeon, Korea

    Cheonsig Sin

Authors
  1. Sangwoo Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Myungjun Jin
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Bonhyun Koo
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Cheonsig Sin
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Sunwoo Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Sunwoo Kim.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lee, S., Jin, M., Koo, B. et al. Pascal’s triangle-based range-free localization for anisotropic wireless networks. Wireless Netw 22, 2221–2238 (2016). https://doi.org/10.1007/s11276-015-1095-9

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11276-015-1095-9

Keywords

Search

Navigation