Journal of Electronic Testing

, Volume 35, Issue 1, pp 45–58 | Cite as

An Optimized NS2 Module for UHF Passive RFID Systems

  • Rahma BenfrajEmail author
  • Vincent Beroulle
  • Nicolas Fourty
  • Aref Meddeb


Radio Frequency Identification (RFID) technology has the potential to dramatically improve numerous industrial practices. However, it still faces many challenges, including tag collisions and reliability, which may limit its use in many application scenarios. In UHF RFID systems, many collisions happen due to the numerous tag responses generated by the inventory process. Also, given the low cost and low performance of UHF RFID tags combined with harsh environments, RFID communications must deal with high Bit-Error-Rate (BER). As a matter of fact, the extra identification delays added by these collisions and communication errors can bring to a waste of bandwidth and more time inventory. The efficiency of tag identification is related to the performance of the anti-collision algorithm. To evaluate this performance, an UHF RFID module has already been developed in the NS2 simulator. This NS2 RFID module implements an RFID system based on the anti-collision Q-Algorithm (Q-Algo) of the EPC Global Protocol Class-1 Generation-2 Standard. In this paper, first, we propose an optimization of this NS2 RFID module by implementing and validating a more realistic version of the Q-Algo. Secondly, we add to this module some fault injection capabilities to evaluate with NS2 the UHF RFID system robustness in presence of communication errors. Finally, we show how this NS2 UHF RFID module is much more realistic for the timing evaluation in presence of communication errors.


UHF RFID Q-algorithm Fault injection NS2 


  1. 1.
    Bagnato G, Maselli G, Petrioli C, Vicari C (2009) Performance analysis of anti-collision protocols for rfid systems. In: Vehicular technology conference, 2009. VTC Spring 2009. IEEE 69th. IEEE, pp 1–5Google Scholar
  2. 2.
    BENFraj R, Beroulle V, Fourty N, Meddeb A (2017) A global approach for the improvement of uhf rfid safety and security. In: 2017 12th international conference on design & technology of integrated systems in nanoscale Era (DTIS). IEEE, pp 1–2Google Scholar
  3. 3.
    Benfraj R, Beroulle V, Fourty N, Meddeb A (2018) Time modeling with ns2 in uhf rfid anti-collision protocols. In: Presented in the 32nd IEEE international conference on advanced information networking and applications (AINA-2018)Google Scholar
  4. 4.
    Chen WT, Kao WB (2011) A novel q-algorithm for epcglobal class-1 generation-2 anti-collision protocol. World Acad Sci Eng Technol 78:801–804Google Scholar
  5. 5.
    Cheng T, Jin L (2007) Analysis and simulation of rfid anti-collision algorithms. In: The 9th international conference on advanced communication technology, vol 1. IEEE, pp 697–701Google Scholar
  6. 6.
    Downard IT (2004) Simulating sensor networks in ns-2. Tech. rep., DTIC DocumentCrossRefGoogle Scholar
  7. 7.
    Durrheim K, Tredoux C (2004) Numbers, hypotheses & conclusions: a course in statistics for the social sciences. Juta and Company LtdGoogle Scholar
  8. 8.
    Finkenzeller K, Handbook R (2010) Fundamentals and applications in contactless smart cards, radio frequency identification and near-field communication. HobokenGoogle Scholar
  9. 9.
    Floerkemeier C, Sarma S (2009) Rfidsim—a physical and logical layer simulation engine for passive rfid. IEEE Trans Autom Sci Eng 6(1):33–43CrossRefGoogle Scholar
  10. 10.
    Fritz G (2012) Simulation de fautes pour l’évaluation du test en ligne de systèmes rfid. Ph.D. thesis, GrenobleGoogle Scholar
  11. 11.
    Global E (2015) Uhf air interface protocol standard generation2/version2Google Scholar
  12. 12.
    Han S, Shin KG, Rosenberg HA (1995) Doctor: An integrated software fault injection environment for distributed real-time systems. In: Proceedings of international conference on computer performance and dependability symposium, 1995. IEEE, pp 204–213Google Scholar
  13. 13.
    Hsueh MC, Tsai TK, Iyer RK (1997) Fault injection techniques and tools. Computer 30(4):75–82CrossRefGoogle Scholar
  14. 14.
    Koren I, Krishna CM (2010) Fault-tolerant systems. ElsevierGoogle Scholar
  15. 15.
    Lee D, Kim K, Lee W (2007) Q+-algorithm: an enhanced rfid tag collision arbitration algorithm. In: International conference on ubiquitous intelligence and computing. Springer, pp 23–32Google Scholar
  16. 16.
    Liu L, Lai S (2006) Aloha-based anti-collision algorithms used in rfid system. In: International conference on wireless communications, networking and mobile computing, 2006. WiCOM 2006. IEEE, pp 1–4Google Scholar
  17. 17.
    Mota RPB, Batista DM (2013) An ns-2 module for simulating passive rfid systems. In: 2013 IEEE 10th international conference on high performance computing and communications & 2013 IEEE international conference on embedded and ubiquitous computing (HPCC_EUC). IEEE, pp 2263–2270Google Scholar
  18. 18.
    Namboodiri V, DeSilva M, Deegala K, Ramamoorthy S (2012) An extensive study of slotted aloha-based rfid anti-collision protocols. Comput Commun 35(16):1955–1966CrossRefGoogle Scholar
  19. 19.
    Niu C, Zhang H, Lin T (2016) An enhanced q algorithm based on epc-c1g2 rfid protocolGoogle Scholar
  20. 20.
    Woellik H (2009) A simulation tool for rfid anti-collision algorithms based on aloha. In: 16th international conference on systems, signals and image processing, 2009. IWSSIP 2009. IEEE, pp 1–4Google Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Rahma Benfraj
    • 1
    • 2
    Email author
  • Vincent Beroulle
    • 1
    • 2
  • Nicolas Fourty
    • 1
    • 2
  • Aref Meddeb
    • 3
  1. 1.Institute of EngineeringUniversity Grenoble AlpesValenceFrance
  2. 2.National Engineering School of TunisUniversity of Tunis EL-ManarTunisTunisia
  3. 3.National Engineering School of SousseUniversity of Sousse, NOCCSSousseTunisia

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