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DEDF: lightweight WSN distance estimation using RSSI data distribution-based fingerprinting

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Abstract

When estimating the distance for wireless sensor networks (WSNs), we always suppose that a fixed curve model exists between the received signal strength indicator (RSSI) and communication distance. But there exist some negative factors in practice, which makes this assumption to contradict with the situation in real communication environment. It results in large distance estimation error with low efficiency. Thus, a lightweight WSN communication distance estimation method is presented, which is called distance estimation using distribution-based fingerprinting. First, we considered the uncertainty in RSSI values, and got the fingerprinting relationship in terms of RSSI data distribution, which is gained through a statistical calculation. Then, a data matching algorithm is implemented to estimate the communication distance. Finally, RSSI values in different conditions are utilized to validate this method. Experimental results demonstrated that the new method can obtain better results with high efficiency than other related methods, and can be applied in WSN localization system.

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Abbreviations

DEDF:

Distance estimation using distribution-based fingerprinting

WSNs:

Wireless sensor networks

RSSI:

Received signal strength indicator

TOA:

Time of arrival

TDOA:

Time different of arrival

AOA:

Angle of arrival

RSSI-d:

Received signal strength indicator-distance

AE:

Absolute error

LS:

Least square

LSLF:

Least square linear fitting

SRLF:

Step regression linear fitting

BP:

Back propagation

LS-SVC:

Least square-support vector classification

References

  1. Jiang JA, Zheng XY, Chen YF et al (2013) A distributed RSS-based localization using a dynamic circle expanding mechanism. IEEE Sens J 13(10):3754–3766

    Article  Google Scholar 

  2. Horng MF, Chen YT, Lo CC, Chu SC, Pan JS (2014) A transmission power optimization with a minimum node degree for energy-efficient wireless sensor networks with full-reachability. Sensors 13(3):3951–3974

    Google Scholar 

  3. Chang CC, Huang YC, Tsai HC (2014) Design and analysis of chameleon hashing based handover authentication scheme for wireless networks. J Inf Hiding Multimed Signal Process 5(1):107–116

    Google Scholar 

  4. Seet BC, Zhang Q, Foh CH, Alvis CM (2012) Hybrid RF mapping and Kalman filtered spring relaxation for sensor network localization. IEEE Sens J 12(5):1427–1435

    Article  Google Scholar 

  5. Luo C, Zhang Yand XIE, Xie W (2014) Traffic regulation based congestion control algorithm in sensor networks. J Inf Hiding Multimed Signal Process 5(2):187–198

    Google Scholar 

  6. Salman N, Ghogho M, Kemp AH (2014) Optimized low complexity sensor node positioning in wireless sensor networks. IEEE Sens J 14(1):39–46

    Article  Google Scholar 

  7. Shih HC, Ho JH, Liao BY, Pan JS (2014) Fault node recovery algorithm for a wireless sensor network. IEEE Sens J 13(7):2683–2689

    Article  Google Scholar 

  8. Luo QH, Yan XZ, Li JB, Peng Y (2014) DDEUDSC: dynamic distance estimation using uncertain data stream clustering in mobile wireless sensor networks. Measurement 55:423–433

    Article  Google Scholar 

  9. Shao HJ, Zhang XP, Wang Z (2014) Efficient closed-form algorithms for AOA based self-localization of sensor nodes using auxiliary variables. IEEE Trans Signal Process 62(10):2580–2594

    Article  MathSciNet  Google Scholar 

  10. Luo QH, Peng Y, Peng XY, Saddik AE (2014) Uncertain data clustering-based distance estimation in wireless sensor networks. Sensors 14(4):6584–6605

    Article  Google Scholar 

  11. Gasparri A, Pascucci F (2014) An interlaced extended information filter for self-localization in sensor networks. IEEE Trans Mobile Comput 9(10):1491–1504

    Article  Google Scholar 

  12. Guo H, Low KS, Nguyen HA (2011) Optimizing the localization of a wireless sensosr network in real time based on a low-cost microcontroller. IEEE Trans Indus Electron 58(3):741–749

    Article  Google Scholar 

  13. Liu TH, Yi SC, Wang XW (2013) A fault management protocol for low-energy and efficient wireless sensor networks. J Inf Hiding Multimed Signal Process 4(1):34–45

    Google Scholar 

  14. Peng Y, Luo QH, Peng XY (2012) WSN localization method using interval data clustering. Acta Autom Sin 38(7):1190–1199

    Article  Google Scholar 

  15. Li Z, Trapp W, Zhang Y, Nath B (2005) Robust statistical methods for securing wireless in sensor networks. In: Proceedings of the international symposium on information processing sensor networks, pp 91–98. doi:10.1109/IPSN.2005.1440903

  16. Stoyanova T, Kerasiotis F, Prayati A, Papadopoulos G (2007) Evaluation of impact factors on RSS accuracy for localization and tracking applications. In: Proceedings of international symposium on mobility management and wireless access (MobiWac2007), pp 9–17. doi:10.1145/1298091.1298094

  17. Kung H, Lin C, Lin T, Vlah D (2009) Localization with snap-inducing shaped residuals (SISR): coping with errors in measurement. In: Proceedings of the annual international conference on mobile computing and networking (MobiCom2009), pp 333–334. doi:10.1145/1614320.1614357

  18. Yaghoubi F, Abbasfar AA, Maham B (2014) Energy-efficient RSSI-based localization for wireless sensor networks. IEEE Commun Lett 18(6):973–976

    Article  Google Scholar 

  19. Huang CH, Lee LH, Ho CC et al (2015) Real-time RFID indoor positioning system based on Kalman-filter drift removal and Heron-bilateration location estimation. IEEE Trans Instrum Meas 64(3):828–839

    Google Scholar 

  20. Bahl P, Padmanabhan VN (2000) RADAR: an in-building RF-based user location and tracking system. In: Proceedings of IEEE INFOCOM 2000, vol 2, pp 775–784

  21. Zhang XF, Cui QM, Shi YL, Tao XF (2013) Robust localisation algorithm for solving neighbour position ambiguity. Electr Lett 49(7):1106–1107

    Article  Google Scholar 

  22. Chiang YY, Hsu WH, Yeh SC, et al (2012) Fuzzy support vector machines for device-free localization. In: Proceedings of IEEE International Instrumentation and measurement technology conference, pp 2169–2172. doi:10.1109/I2MTC.2012.6229338

  23. Luo ZX, Min PS (2013) Survey of target localization methods in wireless sensor networks. In: Proceedings of IEEE international conference on networks, pp 1–4. doi:10.1109/ICON.2013.6781987

  24. Nazir U, Arshad MA, Shahid N, Raza SH (2012) Classification of localization algorithms for wireless sensor network: a survey. In: Proceedings of international conference on open source systems and technologies, pp 1–5. doi:10.1109/ICOSST.2012.6472830

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Acknowledgments

The research presented in this paper is supported by National Natural Science Foundation of China (61102038), Space support technology fund projects (2014-HT-HGD5), Research Fund of Harbin institute of technology (WeiHai) (HIT (WH) 201306, HIT (WH) 201307), Guangxi Key Laboratory of Automatic Detecting Technology and Instruments (YQ14205, YQ15203), Natural Scientific Research Innovation Foundation in Harbin Institute of Technology (HIT.NSRIF.2015122) and State Key Laboratory of Geo-information Engineering (SKLGIE2014-M-2-4).

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Correspondence to Xiaozhen Yan.

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Luo, Q., Yan, X., Li, J. et al. DEDF: lightweight WSN distance estimation using RSSI data distribution-based fingerprinting. Neural Comput & Applic 27, 1567–1575 (2016). https://doi.org/10.1007/s00521-015-1956-2

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  • DOI: https://doi.org/10.1007/s00521-015-1956-2

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