KSII Transactions on Internet and Information Systems (TIIS)

Korean Society for Internet Information (한국인터넷정보학회)
권호 표지
DOI QR코드

DOI QR Code

Rethinking of the Uncertainty: A Fault-Tolerant Target-Tracking Strategy Based on Unreliable Sensing in Wireless Sensor Networks

  • Xie, Yi (Science and Technology Information Systems Engineering Laboratory National University of Defense Technology) ;
  • Tang, Guoming (Science and Technology Information Systems Engineering Laboratory National University of Defense Technology) ;
  • Wang, Daifei (Science and Technology Information Systems Engineering Laboratory National University of Defense Technology) ;
  • Xiao, Weidong (Science and Technology Information Systems Engineering Laboratory National University of Defense Technology) ;
  • Tang, Daquan (Science and Technology Information Systems Engineering Laboratory National University of Defense Technology) ;
  • Tang, Jiuyang (Science and Technology Information Systems Engineering Laboratory National University of Defense Technology)
  • Received : 2012.03.09
  • Accepted : 2012.06.14
  • Published : 2012.06.30
Download PDF
⟨ Previous Next ⟩

Abstract

Uncertainty is ubiquitous in target tracking wireless sensor networks due to environmental noise, randomness of target mobility and other factors. Sensing results are always unreliable. This paper considers unreliability as it occurs in wireless sensor networks and its impact on target-tracking accuracy. Firstly, we map intersection pairwise sensors' uncertain boundaries, which divides the monitor area into faces. Each face has a unique signature vector. For each target localization, a sampling vector is built after multiple grouping samplings determine whether the RSS (Received Signal Strength) for a pairwise nodes' is ordinal or flipped. A Fault-Tolerant Target-Tracking (FTTT) strategy is proposed, which transforms the tracking problem into a vector matching process that increases the tracking flexibility and accuracy while reducing the influence of in-the-filed factors. In addition, a heuristic matching algorithm is introduced to reduce the computational complexity. The fault tolerance of FTTT is also discussed. An extension of FTTT is then proposed by quantifying the pairwise uncertainty to further enhance robustness. Results show FTTT is more flexible, more robust and more accurate than parallel approaches.

Keywords

References

  1. D. Li, K. Wong, Y.H. Hu and A. Sayeed, "detection. classification and tracking of targets in distributed sensor networks, " IEEE Signal Processing Magazine, vol.19, no.2, 2002.
  2. A. Smith, H. Balakrishnan, M. Goraczkoet and N. Priyantha, "tracking moving devices with the cricket location system," MobiSys'04 , pp.190-202, 2004.
  3. F. Gustaffsson and F. Gunnarsson, "mobile positioning using wireless network: possibilities and fundamental limitations based on available wireless network measurements," IEEE Signal Processing Magazine, vol.22, no.4, 2005.
  4. B. Kusy, A. Ledeczi and X. Koutsoukos, "Tracking mobile nodes using RF Doppler Shifts," Sensys'07, pp.29-42, 2007.
  5. S. Mohanty, "VEPSD: A novel velocity estimation algorithm for next- generation wireless systems," IEEE Trans. on Wireless Com., vol.4, no.6, 2005.
  6. A. Terzis, A. Anandarajah, K. More and I.J. Wang, "Slip surface localization in wireless sensor networks for landslide prediction," IPSN'06, pp.109-116, 2006.
  7. W. Xi, Y. He, Y.H. Liu, J.Z. Zhao, L.F. Mo, Z. Yang, J.L. Wang and X.Y. Li, "Locating sensors in the wild: pursuit of ranging quality," Sensys'10, pp.295-308, 2010.
  8. Q.Q. Ren, J.Z. Li and S.Y. Cheng, "target tracking under uncertainty in wireless sensor networks," IEEE ACM Trans. Networking, MASS'11, pp.430-439, 2011.
  9. G. Zanca, F. Zorzi, A. Zanella, and M. Zorzi, "Experimental comparison of rssi-based localization algorithms for indoor wireless sensor networks," RealWSN'08, pp.1-5, 2008.
  10. W. Wang, V. Srinivasan, B. Wang and K.C. Chua, "coverage for target localization in wireless sensor networks," IEEE Trans. on Wireless Comm., vol.7, no.2, pp.667-676, 2008. https://doi.org/10.1109/TWC.2008.060611
  11. B. Gaddi, H. Bracha, A. Tal, D. Danny and R. Boris, "continuous close-proximity rssi-based tracking in wireless sensor networks," in Proc. of 2010 Int'l Conf. on Body Sensor Networks, pp.234-239, 2010.
  12. D. Moore, J. Leonard, D. Rus and S. Teller, "Robust distributed network localization with noisy range measurements," in Proc. of SenSys'04, 2004.
  13. K. Whitehouse, C. Karlof and D. Culler, "A Practical Evaluation of Radio Signal Strength for Ranging-based Localization," SigMobile'07, vol.11, no.1, 2007.
  14. Z.J. Wang, E. Bulut and B.K. Szymanski, "distributed energy-efficient target tracking with binary sensor networks," TOSN'10, vol.6, no.4, 2010.
  15. Z. Abbasi1, A. Farahi and H. H. S. Javadi, "An improvement in maximum likelihood estimation algorithm in sensor networks," International Journal of Computer Science & Engineering Survey, vol.2, no.1, Feb.2011.
  16. X.R. Li and V.P. Jilkov, "A survey of maneuvering target tracking: approximation techniques for nonlinear filtering," SPIE'04, 2004.
  17. P. Zhang and M. Martonosi, "LOCALE: collaborative localization estimation for sparse mobile sensor networks," IPSN'08, 2008.
  18. R.E. Kalman, "A new approach to linear filtering and prediction problems," Trans. ASME, Journal of Basic Engineering, 1960.
  19. B. Ristic, S. Arulampalam and N. Gordon, "Beyond the Kalman Filter: Particle Filters for Tracking Applications," 2004.
  20. J. Liu, J. Reich and F. Zhao, "Collaborative in-network processing for target tracking," Journal on Applied Signal Processing, Mar.2003.
  21. J. Ting, H. Snoussi and C. Richard, "Decentralized variational filtering for target tracking in binary sensor networks," IEEE Trans. on Mobile Computing, vol.9, no.10, pp.1465-1477, 2010. https://doi.org/10.1109/TMC.2010.117
  22. Z. Zhong, T. Zhu, D. Wang and T. He, "Tracking with Unreliable Node Sequences," IEEE InfoCom'09, pp.1215-1223, April 2009.
  23. Z. Zhong and T. He, "MSP: Multi-Sequence Positioning of Wireless Sensor Nodes," Sensys'07, 2007.
  24. K. Yedavalli and B. Krishnamachari, "Sequence-Based Localization in Wireless Sensor Networks," IEEE Trans. on Mobile Computing, vol.7, no.1, pp.81-94, 2008. https://doi.org/10.1109/TMC.2008.4387797
  25. D.B. Johnson and D.A. Maltz, "Dynamic Source Routing in Ad hoc Wireless Networks," IEEE Trans. on Mobile Computing, 1996.
  26. H. Lord, W.S. Gatley and H.A. Evensen, "Noise Control For Engineers", McGraw Hill Book Co., 1980.
  27. C.S.Ogilvy, "Excursions in Geometry", Dover, 1990.
  28. D. M. OFRIM, D. I. SACALEANU, B. A. OFRIM and R. STOIAN, "Implementation of an Adaptive Synchronizing Protocol for Energy Saving in Wireless Sensor Networks," International Journal of Communications, vol.4, no.4, 2010.
  29. G.M. Tang, G.X. Zhou, Y. Xie, D.Q. Tang and J.Y. Tang, "Target Localization Based on Double-level Grid Division in Wireless Sensor Networks," Computer Science, vol.39, no.6, pp.25-29, 2012.
  30. D.B. Johnson and D.A. Maltz," Dynamic Source Routing in Ad hoc Wireless Networks", IEEE Trans. on Mobile Computing, 1996.

Cited by

  1. A Received Signal Strength-based Primary User Localization Scheme for Cognitive Radio Sensor Networks Using Underlay Model-based Spectrum Access vol.8, pp.8, 2012, https://doi.org/10.3837/tiis.2014.08.005