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Energy Efficient Routing Protocol for Ambient Assisted Living Environment

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Abstract

Ambient assisted living (AAL) is focused on providing assistance to patients primarily in their natural environment to improve their quality of life. AAL domain has evolved at a fast pace as the stakeholders of AAL include patients and their relatives, social services, and care givers. AAL follows a multi-tier architecture where data from body area sensor network (BAN) gets routed through the coordinator of such networks via cellular devices or display co-ordinators at hospitals to a remote server over the Internet. A BAN configuration comprises of wearable and/or implantable sensors attached to a patient that are connected to a coordinator node carried by the patient. Though many routing protocols are proposed for routing within BAN, the challenges behind routing data from the coordinator of BAN to the cellular devices or display co-ordinators at hospitals is hardly investigated. But this routing is important for establishing end-to-end communication in AAL. Consequently, in this paper, we propose a multi-hop routing protocol that routes data from body sensor networks to the cellular devices or display co-ordinators. In a hospital scenario, there can be multiple display co-ordinators in vicinity of a coordinator of BAN, thus making this routing problem multi-sink one. Moreover, in a hospital, there can be multiple patients having wearable or implantable sensors attached to them forming multiple BAN configurations in vicinity. Thus, packet transmission from BAN coordinator may interfere with the transmission of a neighboring one. The proposed routing protocol is designed to avoid such inter BAN interference. The protocol is simulated using Castalia simulator and results show that the proposed protocol achieves better balance between energy efficiency and throughput as compared to state-of-the-art algorithms.

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References

  1. Internet of Things (IoT) Healthcare Market is Expected to Reach $136.8 Billion Worldwide, by 2021, Telegraph India, April 12, 2016. https://www.telegraphindia.com/pressrelease/prnw/11662/internet-of-things-iot-healthcare-market-is-expected-to-reac.html. Last accessed 01 February 2018.

  2. Rashidi, P., & Mihailidis, A. (2013). A survey on ambient assisted living tools for older adults. IEEE Journal of Biomedical and Health Informatics, 17(3), 579–590.

    Article  Google Scholar 

  3. Movassaghi, S., Abolhasan, M., & Lipman, J. (2012). Energy efficient thermal and power aware (ETPA) routing in body area networks. In IEEE 23rd international symposium on personal indoor and mobile radio communications (PIMRC) (pp. 1108–1113).

  4. Wang, K., Yun, S., Shu, L., Han, G., & Zhu, C. (2015). LDPA: A local data processing architecture in ambient assisted living communications. IEEE Communications Magazine, 53(1), 56–63.

    Article  Google Scholar 

  5. Khan, R. A., Mohammadani, K. H., Soomro, A. A., Hussain, J., Khan, S., Arain, T. H., et al. (2018). An energy efficient routing protocol for wireless body area sensor networks. Springer Wireless Personal Communications, 99, 1443–1454.

    Article  Google Scholar 

  6. Javaid, N., Ahmad, A., Nadeem, Q., Imran, M., & Haider, N. (2015). iMSIMPLE: iMproved stable increased throughput multi-hop link efficient routing protocols for wireless body area network. Computers in Human Behavior, 51, 1003–1011.

    Article  Google Scholar 

  7. Bag, A., & Bassiouni, M. (2007). Hotspot preventing routing algorithm for delay sensitive biomedical sensor networks. In IEEE international conference on portable information devices (PORTABLE 07)’, IEEE international conference (pp. 1–5).

  8. Tang, Q., Tummala, N., Gupta, S. K., & Schwiebert, L. (2005). Communication scheduling to minimize thermal effects of implanted biosensor networks in homogeneous tissue. IEEE Transactions on Biomedical Engineering, 52, 1285–1294.

    Article  Google Scholar 

  9. Bag, A., & Bassiouni, M. A. (2006). Energy efficient thermal aware routing algorithms for embedded biomedical sensor networks. In IEEE transactions on mobile adhoc and sensor systems (MASS), (Vancouver) (pp. 604–609).

  10. Takahashi, D., Xiao, Y., Hu, F., Chen, J., & Sun, Y. (2007). Temperature-aware routing for telemedicine applications in embedded biomedical sensor networks. EURASIP Journal of Wireless Communications and Networking, 2008, 1–11.

    Google Scholar 

  11. Razzaque, M. A., Hong, C. S., & Lee, S. (2011). Data-centric multiobjective QOS-aware routing protocol for body sensor networks. Sensors, 11(1), 917–937.

    Article  Google Scholar 

  12. Djenouri, D., & Balasingham, I. (2009). New QoS and geographical routing in wireless biomedical sensor networks. In 6th international conference on broadband communications, networks, and systems (BROADNETS) (pp. 1–8).

  13. Liang, X., Balasingham, I., & Byun, S. (2008). A reinforcement learning based routing protocol with QoS support for biomedical sensor networks. In 1st international symposium on applied sciences on biomedical and communication technologies (ISABEL’08) (pp. 1–5).

  14. Braem, B., Latre, B., Blondia, C., Moerman, I., & Demeester, P. (2008). Improving reliability in multi-hop body sensor networks. In 2nd international conference on IEEE sensor technologies and applications, 2008, (SENSORCOMM’08) (pp. 342–347).

  15. Braem, B., Latre, B., Moerman, I., Blondia, C., & Demeester, P. (2006). The wireless autonomous spanning tree protocol for multihop wireless body area networks. In 3rd Annual international conference on mobile and ubiquitous systems: Networking services (pp. 1–8).

  16. Ruzzelli, A. G., Jurdak, R., O’Hare, G. M., & Van Der Stok, P. (2007). Energy-efficient multi-hop medical sensor networking. In 1st ACM SIGMOBILE international workshop on systems and networking support for healthcare and assisted living environments (HealthNet) (pp. 37–42).

  17. Bag, A., & Bassiouni, M. A. (2009). Biocomm—A cross-layer medium access control (mac) and routing protocol co-design for biomedical sensor networks. International Journal of Parallel, Emergent and Distributed Systems, 24(1), 85–103.

    Article  MathSciNet  Google Scholar 

  18. Khan, Z., Sivakumar, S., Phillips, W., & Aslam, N. (2014). A new patient monitoring framework and energy-aware peering routing protocol (epr) for body area network communication. Springer Journal of Ambient Intelligence and Humanized Computing, 5, 409–423.

    Article  Google Scholar 

  19. Chowdhury, C., Aslam, N., Spinsante, S., Perla, D., Campo, A. D., & Gambi, E. (2017). Energy efficient communication in ambient assisted living. In C. Dobre, C. X. Mavromoustakis, N. M. Garcia, R. I. Goleva, G. Mastorakis (Eds.), Ambient assisted living and enhanced living environments: Principles, technologies and control (pp. 37–59). Elsevier.

  20. Jacobsen, R. H., Kortermand, K., Zhang, Q., & Toftegaard, T. S. (2012). Understanding link behavior of non-intrusive wireless body sensor networks. Springer Wireless Personal Communications, 64, 561–582.

    Article  Google Scholar 

  21. Mallick, A., Chowdhury, C., & Saha, A. (2016). Energy efficient routing protocol for ambient assisted living environment with multiple sinks. In 13th international IEEE India conference (INDICON 2016) (pp. 1–6).

  22. Shih, H. C., & Ching, Y. H. (2013). Coloring-based inter-WBAN scheduling for mobile wireless body area networks. IEEE Transactions on Parallel and Distributed Systems, 24(2), 250–259.

    Article  Google Scholar 

  23. Han, Y., Jin, Z., Cho, J., & Kim, T.-S. (2014). A prediction algorithm for coexistence problem in multiple-WBAN environment. International Journal of Distributed Sensor Networks, 11(3), 1–8.

    Google Scholar 

  24. Roy, M., Chowdhury, C., & Aslam, N. (2017). Designing 2-hop interference aware energy efficient routing (HIER) protocol for wireless body area networks, COMSNETS 2017 highlights, LNCS (pp. 1–22). Springer.

  25. Lu, Y. M., & Wong, V. W. S. (2007). An energy-efficient multipath routing protocol for wireless sensor networks. International Journal of Communication Systems, 20(7), 746–766.

    Google Scholar 

  26. Kaur, N., & Singh, S. (2017). Optimized cost effective and energy efficient routing protocol for wireless body area networks. Ad Hoc Networks Journal, 61, 65–84.

    Article  Google Scholar 

  27. Curtis, D., Shih, E., Waterman, J., Guttag, J., Bailey, J., Stair, T., et al. (2008) Physiological signal monitoring in the waiting areas of an emergency room. In ICST 3rd international conference on body area networks (pp. 5:1–8).

  28. Jiang, S., Cao, Y., Lyengar, S., Kuryloski, P., Jafari, R., Xue, Y., et al. (2008) CareNet: An integrated wireless sensor networking environment for remote healthcare. In ICST 3rd international conference on body area networks (BodyNets‘08) (pp. 9:1–3).

  29. Wood, A., Virone, G., Doan, T., Cao, Q., Selavo, L., Wu, Y., et al. (2006) ALARM-NET: Wireless sensor networks for assisted living and residential monitoring. Technical Report, University of Virginia, Computer Science Department.

  30. Huang, L., Yang, Y., Shen, C., & Cui, C. (2016). Research on grey model-based node trajectory prediction in WBAN. International Journal of Sensor Networks, 21(3), 189–196.

    Article  Google Scholar 

  31. Watteyne, T., Auge-Blum, I., Dohler, M., & Barthel, D. (2007). Anybody: A self-organization protocol for body area networks. In ICST 2nd international conference on body area networks (BodyNets), 5 (pp. 8020–8024).

  32. Moh, M., Culpepper, B. J., Dung, L., Moh, T. S., Hamada, T., & Su, C. F. (2005). On data gathering protocols for in-body biomedical sensor networks. In Global telecommunications conference, IEEE GLOBECOM’05, 5 (pp. 2991–2996).

  33. Ortiz, A. M., Ababneh, N., Timmons, N., & Morrison, J. (2012). Adaptive routing for multihop IEEE 802.15.6 wireless body area networks. In 20th international conference on software, telecommunications and computer networks (SoftCOM) (pp. 1–5).

  34. Lu, Y. M., & Wong, V. W. S. (2007). An energy-efficient multipath routing protocol for wireless sensor networks. International Journal of Communication Systems, 20(7), 747–766.

    Article  Google Scholar 

  35. Hayajneh, T., Almashaqbeh, G., Ullah, S., & Vasilakos, A. V. (2014). A survey of wireless technologies coexistence in WBAN: Analysis and open research issues. Wireless Networks, 20(8), 2165–2199.

    Article  Google Scholar 

  36. Le, T. T., & Moh, S. (2017). Link scheduling algorithm with interference prediction for multiple mobile WBANs. Sensors, 17(10), 2231.

    Article  Google Scholar 

  37. Boulis, A. (2018). Castalia user manual. https://github.com/boulis/Castalia. Last Accessed on 01 February, 2018.

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Correspondence to Chandreyee Chowdhury.

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Mallick, A., Saha, A., Chowdhury, C. et al. Energy Efficient Routing Protocol for Ambient Assisted Living Environment. Wireless Pers Commun 109, 1333–1355 (2019). https://doi.org/10.1007/s11277-019-06615-4

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