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Optimal GTS distribution to heterogeneous sensors in IEEE 802.15.4 network for healthcare monitoring applications

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Abstract

In the Low Rate Wireless Personal Area Networks (LR-WPANs), such as Wireless Body Area Networks (WBANs), the tiny sensors implanted in human bodies generate heterogeneous physiological traffic which in turn needs to be sent to the gateway nodes in real-time. The beacon-enabled mode of IEEE 802.15.4 MAC protocol is considered suitable for such types of networks because of its unique Guaranteed Time Slots (GTSs) mechanism. However, Personal Area Network (PAN) coordinator of IEEE 802.15.4 MAC uses a static First-Come-First-Served (FCFS) mechanism to allocate GTSs. This kind of biased and static allocation of GTSs results in poor utilization of the available bandwidth, thus preventing from the real-time data delivery of the sensor packets to the destination. In order to alleviate this problem, we in this paper, propose a novel and effective means of GTS allocation for WBANs, called Dynamic Distribution of GTS Scheme (DDGS) protocol in which the contending nodes are granted GTS slots on a priority basis purely decided by the real-time nature of the traffic in the sensor field. Through extensive simulations, we show that our proposed DDGS protocol significantly outperforms the static allocation of the limited and available contention free slots in respect of bandwidth utilization, network throughput and end-to-end latency without consuming significant energy of sensor nodes.

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References

  1. Alam MM, Hamida EB (2014) Surveying wearable human assistive technology for life and safety critical applications: Standards, challenges and opportunities. Sensors 14(5):9153–9209

    Article  Google Scholar 

  2. Na C, Yang Y, Mishra A (2008) An optimal GTS scheduling algorithm for time-sensitive transactions in IEEE 802.15.4 networks. Comput Netw 52(13):2543–2557

    Article  Google Scholar 

  3. Movassaghi S, Abolhasan M, Lipman J, Smith D, Jamalipour A (2014) Wireless body area networks: a survey. IEEE Commun Surv Tutorials 16(3):1658–1686

    Article  Google Scholar 

  4. Latré B., Braem B, Moerman I, Blondia C, Demeester P (2011) A survey on wireless body area networks. Wirel Netw 17(1):1–18

    Article  Google Scholar 

  5. Wang S, Park JT (2009) Modeling and analysis of multi-type failures in wireless body area networks with semi-markov model. IEEE Commun Lett 14(1):6–8

    Article  Google Scholar 

  6. Group IW et al (2011) IEEE standard for local and metropolitan area networks part 15.4: low-rate wireless personal area networks (lr-wpans). IEEE Std 802:4–2011

    Google Scholar 

  7. Shah RC, Yarvis M (2006) Characteristics of on-body 802.15. 4 networks. In: 2006 2nd IEEE workshop on wireless mesh networks. IEEE, pp 138–139

  8. Negra R, Jemili I, Belghith A (2016) Wireless body area networks: applications and technologies. Procedia Comput Sci 83:1274–1281

    Article  Google Scholar 

  9. Koubaa A, Alves M, Tovar E (2006) GTS allocation analysis in IEEE 802.15.4 for real-time wireless sensor networks. In: Proceedings 20th IEEE international parallel & distributed processing symposium. IEEE, pp 8–16

  10. Timmons NF, Scanlon WG (2004) Analysis of the performance of IEEE 802.15.4 for medical sensor body area networking. In: 2004 first annual IEEE communications society conference on sensor and Ad Hoc communications and networks, 2004. IEEE SECON 2004. IEEE, pp 16–24

  11. Sixto C, Jorge L (2017) Scheduling the real-time transmission of periodic measurements in 802.15.4 wireless sensor network. Procedia Comput Sci 114:499–506

    Article  Google Scholar 

  12. Shrestha B, Hossain E, Camorlinga S (2011) IEEE 802.15.4 MAC with GTS transmission for heterogeneous devices with application to wheelchair body-area sensor networks. IEEE Trans Inf Technol Biomed 15 (5):767–777

    Article  Google Scholar 

  13. Cheng L, Zhang X, Bourgeois A (2007) GTS allocation scheme revisited. Electron Lett 43 (18):1005–1006

    Article  Google Scholar 

  14. Al Rasyid MUH, Lee BH, Sudarsono A (2013) PEGAS: Partitioned GTS allocation scheme for IEEE 802.15.4 networks. In: 2013 international conference on computer, control, informatics and its applications (IC3INA). IEEE, pp 29–32

  15. Lee BH, Wu HK, Yu NC (2018) A priority based algorithm for adaptive superframe adjustment and GTS allocation (PASAGA) in IEEE 802.15.4 LR-WAN. In: 2018 IEEE international conference on applied system invention (ICASI). IEEE, pp 318–320

  16. Lee H, Lee K, Shin Y (2012) A GTS allocation scheme for emergency data transmission in cluster-tree WSNs. In: 2012 14th international conference on advanced communication technology (ICACT). IEEE, pp 675–678

  17. Lei X, Choi YH, Park S, Rhee SH (2012) GTS allocation for emergency data in low-rate WPAN. In: 2012 18th asia-pacific conference on communications (APCC). IEEE, pp 792–793

  18. El Gholami K, Hou KM, Elkamoun N, Shi HL, Liu X (2015) Real World performance evaluation of FF-MAC Protocol for Real-Time Data Forwarding in WSN. Wirel Pers Commun 82(4):2017–2031

    Article  Google Scholar 

  19. Koubaa A, Alves M, Tovar E (2006) i-GAME: an implicit GTS allocation mechanism in IEEE 802.15.4 for time-sensitive wireless sensor networks. In: 18th euromicro conference on real-time systems (ECRTS’06). IEEE, pp 183–192

  20. Zhang H, Xin S, Yu R, Lin Z, Guo Y (2009) An adaptive GTS allocation mechanism in IEEE 802.15.4 for various rate applications. In: 2009 fourth international conference on communications and networking in China. IEEE, pp 1–5

  21. Huang YK, Pang AC, Hung HN (2008) An adaptive GTS allocation scheme for IEEE 802.15.4. IEEE Trans Parallel Distrib Syst 19(5):641–651

    Article  Google Scholar 

  22. Xia F, Hao R, Li J, Xiong N, Yang LT, Zhang Y (2013) Adaptive GTS allocation in IEEE 802.15.4 for real-time wireless sensor networks. J Syst Archit 59(10):1231–1242

    Article  Google Scholar 

  23. Shah SK, Rane SJ, Vishwakarma DD (2014) GTS allocation strategy for IEEE 802.15.4 WSN. In: 2014 international conference on IT convergence and security (ICITCS). IEEE, pp 1–5

  24. Al-Anbagi I, Erol-Kantarci M, Mouftah HT (2015) Delay critical smart grid applications and adaptive QoS provisioning. IEEE Access 3:1367–1378

    Article  Google Scholar 

  25. Kim S, Lee JH, Eom DS (2014) An adaptive beaconing MAC protocol providing energy-efficient healthcare service. Wirel personal Commun 75(4):1915–1936

    Article  Google Scholar 

  26. Le NT, Choi S, Jang YM (2012) A new QoS resource allocation scheme using GTS for WPANs. Wirel Pers Commun 67(1):25–45

  27. Ho CL, Lin CH, Hwang WS, Chung SM (2012) Dynamic GTS allocation scheme in IEEE 802.15.4 by multi-factor. In: 2012 eighth international conference on intelligent information hiding and multimedia signal processing. IEEE, pp 457–460

  28. Bouazzi I, Bhar J, Atri M (2018) A dynamic adaptation mechanism for traffic conditions in wireless sensor network. Wirel Pers Commun 101(4):1967–1982

    Article  Google Scholar 

  29. Yazdi FR, Hosseinzadeh M, Jabbehdari S (2019) A priority-based MAC protocol for energy consumption and delay guaranteed in wireless body area networks. Wirel Pers Commun 108(3):1677–1696

    Article  Google Scholar 

  30. Roy S, Mallik I, Poddar A, Moulik S (2017) PAG-MAC: Prioritized allocation of GTSs in IEEE 802.15.4 MAC protocol-a dynamic approach based on analytic hierarchy process. In: 2017 14th IEEE india council international conference (INDICON). IEEE, pp 1–6

  31. Noga J, Sarbua V (2005) An online partially fractional knapsack problem. In: 8th international symposium on parallel architectures, algorithms and networks (ISPAN’05). IEEE, pp 108–112

  32. Castalia A (2009) Simulator for wireless sensor networks and body area networks. User Manual

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Pondicherry Engineering College, Puducherry, India

    Gulshan Soni & Kandasamy Selvaradjou

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  1. Gulshan Soni
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  2. Kandasamy Selvaradjou
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Correspondence to Gulshan Soni.

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Soni, G., Selvaradjou, K. Optimal GTS distribution to heterogeneous sensors in IEEE 802.15.4 network for healthcare monitoring applications. Pers Ubiquit Comput 26, 131–153 (2022). https://doi.org/10.1007/s00779-021-01643-z

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  • DOI: https://doi.org/10.1007/s00779-021-01643-z

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