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Applying Cubic Spline Method to Estimate the Number of RFID Tags in Error-Prone Communication Channels

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Radio frequency identification systems aid in fast identification of tagged objects simultaneously, by means of radio signals. However, when radio frequency signals are emitted simultaneously, there is a probability of collision occurrence because of which the identification process may fail, and thereby resulting in a waste of resources. Therefore, several anti-collision algorithms have been proposed to reduce the probability of collision occurrence. In almost all the existing anti-collision algorithms, a prior knowledge of the number of tags has a significant effect on the efficiency of the algorithms. However, since the exact number of tags is unavailable, it is essential to develop an accurate tag estimation method to reduce the collision probability. In this paper, the authors present a novel tag estimation method, which estimates the number of tags by means of the captured number of idle slots, by applying the cubic spline technique. Besides presenting highly accurate estimation results, this method also demonstrates compatibility with error-prone communication channels. Cubic spline method estimates the number of tags accurately, with <1 % error rate. Based on the results, it is observed that more accurate estimation results from the proposed method provides greater channel efficiency and lowers the average identification time.

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  1. 1.

    Symonds, J., Ayoade, J., & Parry, D. (2009). Auto-Identification and ubiquitous computing applications. USA: Information Science Reference.

  2. 2.

    Finkenzeller, K. (2010). RFID Handbook: Fundamentals and applications in contactless smart cards, radio frequency identification and near-field communication (3rd ed.). New York: Wiley Ltd.

  3. 3.

    Shakiba, M., Zavvari, A., & Sundararajan, E. (2011). Fitted dynamic framed slotted ALOHA anti-collision algorithm in RFID systems. In International conference on information technology and multimedia (ICIM) (pp. 1–6). IEEE.

  4. 4.

    Shih, D.-H., Sun, P.-L., Yen, D. C., & Huang, S.-M. (2006). Taxonomy and survey of RFID anti-collision protocols. Computer Communications, 29(11), 2150–2166.

  5. 5.

    Alsalih, W., Ali, K., & Hassanein, H. (2013). A power control technique for anti-collision schemes in RFID systems. Computer Networks, 57(9), 1991–2003.

  6. 6.

    Abramson, N. (1970). THE ALOHA SYSTEM: Another alternative for computer communications. In Proceedings of the November 1719, 1970, fall joint computer conference (pp. 281–285). ACM.

  7. 7.

    Roberts, L. G. (1975). ALOHA packet system with and without slots and capture. ACM SIGCOMM Computer Communication Review, 5(2), 28–42.

  8. 8.

    Deng, D.-J., & Tsao, H.-W. (2011). Optimal dynamic framed slotted ALOHA based anti-collision algorithm for RFID systems. Wireless Personal Communications, 59(1), 109–122.

  9. 9.

    Shakiba, M., Singh, M. J., Sundararajan, E., Zavvari, A., & Islam, M. T. (2014). Extending birthday paradox theory to estimate the number of tags in RFID systems. PLoS One, 9(4), e95425.

  10. 10.

    Joo, Y.-I., Seo, D.-H., & Kim, J.-W. (2013). An efficient anti-collision protocol for fast identification of RFID Tags. Wireless Personal Communications, 77(1), 767–775.

  11. 11.

    Myung, J., Lee, W., Srivastava, J., & Shih, T. K. (2007). Tag-splitting: Adaptive collision arbitration protocols for RFID tag identification. IEEE Transactions on Parallel and Distributed Systems, 18(6), 763–775.

  12. 12.

    Wu, H., Zeng, Y., Feng, J., & Gu, Y. (2013). Binary tree slotted ALOHA for passive RFID tag anticollision. IEEE Transactions on Parallel and Distributed Systems, 24(1), 19–31. doi:10.1109/TPDS.2012.120.

  13. 13.

    Ahson, S. A., & Ilyas, M. (2010). RFID handbook: Applications, technology, security, and privacy. Boca Raton: CRC Press.

  14. 14.

    Wu, H., & Zeng, Y. (2010). Bayesian tag estimate and optimal frame length for anti-collision aloha RFID system. IEEE Transactions on Automation Science and Engineering, 7(4), 963–969.

  15. 15.

    Cui, Y., & Zhao, Y. (2010). A fast zero estimation scheme for RFID systems. Computer Communications, 33(11), 1318–1324.

  16. 16.

    Vales-Alonso, J., Bueno-Delgado, M. V., Egea-López, E., Alcaraz, J. J., & Pérez-Mañogil, J. M. (2011). On the optimal identification of tag sets in time-constrained RFID configurations. Sensors, 11(3), 2946–2960.

  17. 17.

    Vogt, H. (2002). Efficient object identification with passive RFID tags. In F. Mattern & M. Naghshineh (Eds.), Pervasive computing (pp. 98–113). New York: Springer.

  18. 18.

    Qian, C., Ngan, H., Liu, Y., & Ni, L. M. (2011). Cardinality estimation for large-scale RFID systems. IEEE Transactions on Parallel and Distributed Systems, 22(9), 1441–1454.

  19. 19.

    Klair, D. K., Chin, K.-W., & Raad, R. (2010). A survey and tutorial of RFID anti-collision protocols. IEEE Communications Surveys and Tutorials, 12(3), 400–421.

  20. 20.

    Schoute, F. C. (1983). Dynamic frame length ALOHA. IEEE Transactions on Communications, 31(4), 565–568.

  21. 21.

    Bin, Z., Kobayashi, M., & Shimizu, M. (2005). Framed ALOHA for multiple RFID objects identification. IEICE Transactions on Communications, 88(3), 991–999.

  22. 22.

    Cha, J.-R., & Kim, J.-H. (2005) Novel anti-collision algorithms for fast object identification in RFID system. In Proceedings of 11th international conference on parallel and distributed systems (Vol. 2, pp. 63–67). IEEE.

  23. 23.

    Eom, J.-B., & Lee, T.-J. (2010). Accurate tag estimation for dynamic framed-slotted ALOHA in RFID systems. IEEE Communications Letters, 14(1), 60–62.

  24. 24.

    Vogt, H. (2002). Multiple object identification with passive RFID tags. In IEEE international conference on systems, man and cybernetics (Vol. 3, p. 6). IEEE.

  25. 25.

    Chen, W.-T. (2009). An accurate tag estimate method for improving the performance of an RFID anticollision algorithm based on dynamic frame length ALOHA. IEEE Transactions on Automation Science and Engineering, 6(1), 9–15.

  26. 26.

    Tong, Q., Zhang, Q., Min, R., & Zou, X. (2012). Bayesian estimation in dynamic framed slotted ALOHA algorithm for RFID system. Computers and Mathematics with Applications, 64(5), 1179–1186. doi:10.1016/j.camwa.2012.03.060.

  27. 27.

    Rivest, R. L. (1987). Network control by Bayesian broadcast. IEEE Transactions on Information Theory, 33(3), 323–328.

  28. 28.

    Floerkemeier, C. (2007). Bayesian transmission strategy for framed ALOHA based RFID protocols. In IEEE international conference on RFID (pp. 228–235). IEEE.

  29. 29.

    Khandelwal, G., Lee, K., Yener, A., & Serbetli, S. (2007). ASAP: A MAC protocol for dense and time-constrained RFID systems. EURASIP Journal on Wireless Communications and Networking, 2007(2), 3.

  30. 30.

    Kodialam, M., & Nandagopal, T. (2006). Fast and reliable estimation schemes in RFID systems. In Proceedings of the 12th annual international conference on mobile computing and networking (pp. 322–333). ACM.

  31. 31.

    Park, J., & Lee, T.-J. (2012). Error resilient estimation and adaptive binary selection for fast and reliable identification of RFID tags in error-prone channel. IEEE Transactions on Mobile Computing, 11(6), 959–969.

  32. 32.

    Shakiba, M., Sundararajan, E., Zavvari, A., & Islam, M. (2013). Cubic spline-based tag estimation method in RFID multi-tags identification process. Canadian Journal of Electrical and Computer Engineering, 36(1), 11–17.

  33. 33.

    Motwani, R., & Raghavan, P. (2010). Randomized algorithms. London: Chapman & Hall.

  34. 34.

    ISO. (2013). Information technology—Radio frequency identification for item management. Part 6: Parameters for air interface communications at 860 MHz to 960 MHz General (Vol. ISO/IEC 18000-6:2013). ISO.

  35. 35.

    EPCglobal. (2008). EPC™ Radio-Frequency Identity Protocols Class-1 Generation-2 UHF RFID Protocol for Communications at 860 MHz–960 MHz Version 1.2.0. (Vol. Version 1.2.0). EPCglobal.

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Correspondence to Masoud Shakiba.

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Shakiba, M., Singh, M.J., Islam, M.T. et al. Applying Cubic Spline Method to Estimate the Number of RFID Tags in Error-Prone Communication Channels. Wireless Pers Commun 83, 361–382 (2015). https://doi.org/10.1007/s11277-015-2397-z

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  • RFID systems
  • Anti-collision algorithms
  • Framed slotted ALOHA
  • Tag identification
  • Estimation methods
  • Cubic spline interpolation