Wireless Personal Communications

, Volume 101, Issue 3, pp 1519–1537 | Cite as

Enhancement of the Traffic Differentiation Architecture for WBAN Based on IEEE 802.15.4

  • Sabri KhssibiEmail author
  • Adrien Van Den Bossche
  • Hanen Idoudi
  • Leila Azouz Saidane
  • Thierry Val


In the healthcare domain, Wireless Body Area Network has emerged as a vital technology that is capable of providing better methods to diagnose various hazardous diseases. The CANet projet is a project that proposes alternative monitoring solutions. This paper studies the possibility of transmitting different types of information through an IEEE 802.15.4 MAC layer that not supports the transmission of heterogeneous information. We have proposed an extension to the MAC layer which makes possible the transmission of various information types. This solution designed by “diffrentiation layer” uses a purge function to ensure the use of CAP and CFP by the same node in the same superframe and allows the differentiation between several information. Our results show that our solution is reliable under worst-case.


IEEE 802.15.4 QoS E-Health WBAN CANet project 



  1. 1.
    Akyildiz, I. F., Su, W., Sankarasubramaniam, Y., & Cayirci, E. (2002). Wireless sensor networks: A survey. Computer Networks, 38(4), 393–422.CrossRefGoogle Scholar
  2. 2.
    Stankovic, J. (2008). When sensor and actuator networks cover the world. ETRI Journal, 30(5), 627–633.CrossRefGoogle Scholar
  3. 3.
    Al Agha, K., Bertin, M. H., Dang, T., Guitton, A., Minet, P., Val, T., et al. (2009). Which wireless technology for industrial wireless sensors network? the development of ocari technology. IEEE Transactions on Industrial Electronics, 56(10), 13.CrossRefGoogle Scholar
  4. 4.
    Noury, N., Herve, T., Rialle, V., Virone, G., Mercier, E., Morey, G., Moro, A. & Porcheron, T. (2000). Monitoring behavior in home using a smart fall sensor and position sensors. In 1st annual international conference on microtechnologies in medicine and biology, 2000, pp. 607–610.Google Scholar
  5. 5.
    Schwiebert, L., Gupta, SKS., & Weinmann, J. (2001). Research challenges in wireless networks of biomedical sensors. In Proceedings of the 7th annual international conference on mobile computing and networking, MobiCom ’01, pp. 151–165.Google Scholar
  6. 6.
    Eysenbach, G. (2001). What is e-health? Journal of Medical Internet Research, 3(2), 20.CrossRefGoogle Scholar
  7. 7.
    Bougeois, E., Van den Bossche, A., Cazenave, N., Redon, L., Soveja, A., Val, T. & Villemur, T. (2012). Le projet CANet: une activit pluridisciplinaire liant recherche et pdagogie.Google Scholar
  8. 8.
    Val, T., Bougeois, E., Van den Bossche, A., Cazenave, N., Redon, L., Soveja, A. & Villemur, T. (2013). Projet CANet: un systme de suivi de personnes mobilit rduite grce leur canne de marche, Magazine des IUT de France, 10 & 11.Google Scholar
  9. 9., babolat pure drive play: The intelligent racquet at your service. Accessed May 12, 2014.
  10. 10., intelligent racquets to be the new tool for data mining in tennis. Accessed July 12, 2014.
  11. 11.
    Pereira, V., Silva, JS. & Monteiro, E. (2012). A framework for wireless sensor networks performance monitoring. In World of wireless, mobile and multimedia networks (WoWMoM), 2012.Google Scholar
  12. 12.
    Lindh, T. & Orhan, I. (2009). Wireless communication systems: Performance monitoring and control in contention-based wireless sensor networks. In ISWCS 2009.Google Scholar
  13. 13.
    Abreu, C., Miranda, F., Ricardo, M., & Mendes, P. M. (2016). QoS-based management of biomedical wireless sensor networks for patient monitoring. SpringerPlus, 3, 239.CrossRefGoogle Scholar
  14. 14.
    She, H., & Lu, Z. (2007). Network-based system architecture for remote medical applications. Asia-Pacic Advanced Network, China Google Scholar
  15. 15.
    Yoon, J. S., Gahng-Seop, A., Seong-Soon, J. & al. (2010). PNP-MAC: Preemptive slot allocation and non-preemptive transmission for providing QoS in body area networks. In IEEE consumer communications and networking conference (CCNC), pp. 1–15.Google Scholar
  16. 16.
    Hossien, M. (2010). A novel congestion control protocol for vital signs monitoring in wireless biomedical sensor networks. In IEEE WCNC.Google Scholar
  17. 17.
    Kwak, K. S. & Ullah, S. (2010). A traffic-adaptive MAC protocol for WBAN. 2010 IEEE Globecom Workshops, Miami, FL, pp. 1286–1289.Google Scholar
  18. 18.
    George, S., Nikos, D., Rosario, S., Valeria, L., Giancarlo, F., & Yiannis, A. (2016). Decentralized time-synchronized channel swapping for ad hoc wireless networks. IEEE Transactions on Vehicular Technology, 65(10), 8538–8553.CrossRefGoogle Scholar
  19. 19.
    Galzarano, S., Fortino, G. & Liotta, A. (2014). A learning-based mac for energy efficient wireless sensor networks. In Proceedings of the international conference on internet and distributed computing systems, pp. 396–406, Springer.Google Scholar
  20. 20.
    Hämäläinen, M., Iinatti, J., & Mucchi, L. (2014). Wireless UWB body area networks: Using the IEEE802.15.4-2011. London: Academic Press.Google Scholar
  21. 21.
    Young Shin, S. (2013). A novel method for service differentiation in IEEE 802.15.4: Priority jamming. International Journal of Computers Communications Control, 8(1), 127–135.CrossRefGoogle Scholar
  22. 22.
    Khssibi, S., Van den Bossche, A., Val, T., Idoudi, H., & Azzouz Saidane, L. (2017). Optimization of IEEE 802.15.4: Overview theoretical study and simulation. International Journal of Information and Communication Technology, 10(2), 119–135.CrossRefGoogle Scholar
  23. 23.
    Severino, R., Batsa, M., Alves, M. & Koubaa, A. (2010). A traffic differentiation add-on to the IEEE 802.15.4 protocol: Implementation and experimental validation over a real-time operating system in DSD 2010. In Proceedings of the 2010, 13th Euromicro conference on digital system design: Architectures, methods and tools, France, pp. 501–508.Google Scholar
  24. 24.
    Saxena, N., Roy, A., & Shin, J. (2008). Dynamic duty cycle and adaptive contention window based QoS-MAC protocol for wireless multimedia sensor networks. Computer Networks, 52(13), 2532–2542.CrossRefzbMATHGoogle Scholar
  25. 25.
    Firoze, A., Ju, L., & Kwong, L. (2007). PR-MAC a priority reservation MAC protocol for wireless sensor networks. In ICEE 2007: Proceedings of the international conference on electrical engineering, Pakistan, pp. 1–6.Google Scholar
  26. 26.
    Xia, F., Li, J., Hao, R., Kong, X., & Gao, R. (2013). Service differentiated and adaptive CSMA/CA over IEEE 802.15.4 for cyber-physical systems. The Scientific World Journal. Scholar
  27. 27.
    Kim, E., Kim, M., Youm, S. K., Choi, S., & Kang, C. H. (2007). Priority-based service differentiation scheme for IEEE 802.15.4 sensor networks. AEU-International Journal of Electronics and Communications, 61(2), 69–81.CrossRefGoogle Scholar
  28. 28.
    Youn, M. J., Oh, Y. Y., Lee, J. & Kim, Y. (2007). IEEE 802.15.4 based QoS support slotted CSMA/CA MAC for wireless sensor networks. In SENSORCOMM 2007: International conference on sensor technologies and applications, Spain, pp. 113–117.Google Scholar
  29. 29.
    Koubaa, A., Alves, M., Nefzi, B., & Song, Y. Q. (2006). Improving the IEEE 802.15.4 slotted CSMA, CA MAC for time-critical events in wireless sensor networks. In RTN, Proceedings of the workshop on real time networks, Germany, pp. 270–277.Google Scholar
  30. 30.
    Kim, T. H., & Choi, S. (2006). Priority-based delay mitigation for event-monitoring IEEE 802.15.4 LR-WPANs. IEEE Communications Letters, 10(3), 213–215.CrossRefGoogle Scholar
  31. 31.
    Aykut Yigitel, M., Durmaz Incel, O., & Ersoy, C. (2011). QoS-aware MAC protocols for wireless sensor networks: A survey. Computer Networks, 55(8), 1982–2004.CrossRefGoogle Scholar
  32. 32.
    Nguyen, K., Nguyen, T., Chaing, C.K. & Motani, M. (2006). A prioritized MAC protocol for multi-hop, event-driven wireless sensor networks. In ICCE 2006: Proceeding of the first international conference on communications and electronics, pp. 47–52.Google Scholar
  33. 33.
    Liu, Y., Elhanany, I. & Qi, H. (2005). An energy-efficient QoS-aware media access control protocol for wireless sensor networks. In Proceedings of the IEEE international conference on mobile Adhoc and sensor systems conference, pp. 191.Google Scholar
  34. 34.
    Huang, Y. K., Pang, A. C., & Hung, H. N. (2008). An adaptive GTS allocation scheme for IEEE 802.15.4. IEEE Transactions on Parallel and Distributed Systems, 9(5), 641–651.CrossRefGoogle Scholar
  35. 35.
    Villaverde, B. C., Rea, S. & Pesch, D. (2010). D-SeDGAM: A dynamic service differentiation based GTS allocation mechanism for IEEE 802.15.4 WSN. In ITNG 2010: Proceedings of the 7th international conference on information technology: New generations, pp. 852–857.Google Scholar
  36. 36.
    Yuce, M. R. (2016). Ultra-wideband and 60 GHz communications for biomedical applications. Berlin: Springer.Google Scholar
  37. 37.
    Khssibi, S. (2015). Using cane sensor networks for people monitoring applications, Ph.D., University of Jean Jaures.Google Scholar
  38. 38.
    Van den Bossche, A., Dalce, R. & Val, T. (2016). OpenWiNo: An open hardware and software framework for fast-prototyping in the IoT. In International conference on telecommunications, Greece.Google Scholar
  39. 39.
    Lachtar, A., Val, T., & Kachouri, A. (2016). 3DCane: A monitoring system for the elderly using a connected walking stick. International Journal of Computer Science and Information Security, 14(8), 535.Google Scholar
  40. 40.
    Mohamed, A. B. H., Val, T., Andrieux, L., & Kachouri, A. (2014). A help for assisting people based on a depth cameras system dedicated to elderly and dependent people. Journal of Biomedical Engineering and Medical Imaging, Society for Science and Education, 1(6), 51–56.Google Scholar

Copyright information

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

Authors and Affiliations

  1. 1.IRIT, UMR 5505 - CNRSUniversite de ToulouseBlagnac CedexFrance
  2. 2.National School of Computer ScienceUniversity of ManoubaManoubaTunisia

Personalised recommendations