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Modelling Buffer-Overflow in 6LoWPAN-Based Resource-Constraint IoT-Healthcare Network

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Abstract

Healthcare is one of the prominent domains that can benefit from numerous revolutionary features of the Internet of Things. Proactive, personalized, and connected healthcare is promised with the amalgamation of IoT in the healthcare sector. Recent advancements in the Wireless Sensor Network and IPv6 over Low-Power Wireless Personal Area Networks provide hopes for implementing the ‘Internet of Healthcare Things’. Such an application demands real-time, time-critical, instantaneous, zero loss of information at a higher data rate from resource-constraint medical sensing devices. Such requirements create new and never-foreseen challenges in front of researchers. Sincerely addressing congestion for the 6LoWPAN-based resource-limited IoHT network is a severe challenge. This paper discusses the situations of congestion occurrence, the steps required for mitigation, and the factors affecting congestion. As identified, buffer overflow is a discernible cause that leads to congestion and further loss of information. An analytical model that estimates the probability of packet loss incurred due to buffer overflow in patient-centric resource-constraint IoT-healthcare networks has been presented. The buffer-loss probability, the number of packets lost, and the total number of packets received at the local sink are calculated in the results.

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References

  1. Shelby, Z., & Bormann, C. (2009). 6LoWPAN: The wireless embedded internet. Wiley.

    Book  Google Scholar 

  2. Li, S., Xu, L. D., & Zhao, S. (2015). The internet of things: A survey. Information Systems Frontiers, 17, 243–259. https://doi.org/10.1007/s10796-014-9492-7

    Article  Google Scholar 

  3. Khalil, N., Abid, M. R., Benhaddou, D., & Gerndt, M. (2014). Wireless sensors networks for internet of things. In 2014 IEEE ninth international conference on intelligent sensors, sensor networks and information processing (ISSNIP), Singapore (pp. 1–6). https://doi.org/10.1109/ISSNIP.2014.6827681

  4. Ghaffari, A. (2015). Congestion control mechanisms in wireless sensor networks: A survey. Journal of Network and Computer Applications, 52, 101–115. https://doi.org/10.1016/j.jnca.2015.03.002

    Article  Google Scholar 

  5. Gara, F., Ben Saad, L., Ben Ayed, R., & Tourancheau, B. (2015). RPL protocol adapted for healthcare and medical applications. In 2015 International wireless communications and mobile computing conference (IWCMC), Dubrovnik (pp. 690–695). https://doi.org/10.1109/IWCMC.2015.7289167

  6. Di Marco, P., Park, P., Fischione, C., & Johansson, K. H. (2015). Analytical modeling of multi-hop IEEE 802.15.4 networks. IEEE Transactions on Vehicular Technology, 61(7), 3191–3208. https://doi.org/10.1109/ACCESS.2015.2437951

    Article  Google Scholar 

  7. Islam, S. M. R., Kwak, D., & Kabir, M. H. (2009). Less sensor networks. In 2009 IEEE/ACS international conference on computer systems and applications, Rabat (pp. 478–484). https://doi.org/10.1109/AICCSA.2009.5069367

  8. Misra, S., Tiwari, V., & Obaidat, M. S. (2012). Adaptive learning solution for congestion avoidance. Wire. https://doi.org/10.1109/TVT.2012.2201221

    Article  Google Scholar 

  9. Misra, S., Woungang, I., Misra, C., & Subhas, S. (Eds.). (2009). Guide to wireless sensor networks. Springer.

    MATH  Google Scholar 

  10. Pant, N., Singh, M. P., & Kumar, P. (2014). Traffic and resource based methods for congestion control in wireless sensor networks: A comparative analysis. In 2014 IEEE 6th international conference on adaptive science & technology (ICAST), Ota, Nigeria (pp. 1–6). https://doi.org/10.1109/ICASTECH.2014.7068066

  11. Verma, H., Chauhan, N., Chand, N., & Awasthi, L. K. (2022). Buffer-loss estimation to address congestion in 6LoWPAN based resouce-restricted ‘Internet of Healthcare Things’ network. Computer Communications, 181, 236–256. https://doi.org/10.1016/j.comcom.2021.10.016

    Article  Google Scholar 

  12. Kafi, M. A., Djenouri, D., Ben-Othman, J., & Badache, N. (2014). Congestion control protocols in wireless sensor networks: A survey. IEEE Communications Surveys & Tutorials, 16(3), 1369–1390. https://doi.org/10.1109/SURV.2014.021714.00123

    Article  Google Scholar 

  13. Heimlicher, S., Nuggehalli, P., & May, M. (2007). End-to-end versus hop-by-hop transport. SIGMETRICS Performance Evaluation Review, 35(3), 59–60. https://doi.org/10.1145/1328690.1328716

    Article  Google Scholar 

  14. Gebali, F. (2015). Analysis of computer networks (2nd ed.). Springer.

    Book  MATH  Google Scholar 

  15. Winter, T., Thubert, P., Brandt, A., Hui, J., & Kelsey, R. (2012). RPL: IPv6 routing protocol for low-power and lossy networks (p. 6550). IETF:RFC.

    Google Scholar 

  16. Al-Kashoash, H. A. A., Kharrufa, H., Al-Nidawi, Y., et al. (2019). Congestion control in wireless sensor and 6LoWPAN networks: Toward the internet of things. Wireless Networks, 25, 4493–4522. https://doi.org/10.1007/s11276-018-1743-y

    Article  Google Scholar 

  17. Kempa, W. M., & Kobielnik, M. (2018). Time to buffer overflow in a queueing model with working vacation policy. In P. Gaj, M. Sawicki, G. Suchacka, & A. Kwiecien (Eds.), Computer networks. CN 2018. Communications in computer and information science. (Vol. 860). Springer. https://doi.org/10.1007/978-3-319-92459-5_18

    Chapter  MATH  Google Scholar 

  18. Accettura, N., Grieco, L. A., Boggia, G. & Camarda, P. (2011). Performance analysis of the RPL routing protocol. In 2011 IEEE international conference on mechatronics, Istanbul, Turkey (pp. 767–772). https://doi.org/10.1109/ICMECH.2011.5971218

  19. Al-Kashoash, H. A. A., & Kemp, A. H. (2016). Comparison of 6LoWPAN and LPWAN for the internet of things. Australian Journal of Electrical and Electronics Engineering, 13(4), 268–274. https://doi.org/10.1080/1448837X.2017.1409920

    Article  Google Scholar 

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The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.

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HV: Conceptualization, Formal analysis, Investigation, Methodology, Resources, Writing—original draft, Writing—review and editing, Visualization, Validation. NC: Supervision, Conceptualization, Formal analysis, Investigation, Visualization, Validation. LKA: Supervision, Investigation, Visualization, Validation.

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Correspondence to Himanshu Verma, Naveen Chauhan or Lalit Kumar Awasthi.

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Verma, H., Chauhan, N. & Awasthi, L.K. Modelling Buffer-Overflow in 6LoWPAN-Based Resource-Constraint IoT-Healthcare Network. Wireless Pers Commun 129, 1113–1128 (2023). https://doi.org/10.1007/s11277-023-10178-w

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