Advertisement

Node Density Analysis for WBAN Schemes in Terms of Stability and Throughput

  • Sheeraz AhmedEmail author
  • Nouman Sadiq
  • Kamran Sadiq
  • Nadeem Javaid
  • M. Ali Taqi
Chapter
Part of the EAI/Springer Innovations in Communication and Computing book series (EAISICC)

Abstract

Wireless sensor applications have resulted in significant advancements in the medical sector known as body area networks. They are being heavily employed by wearable monitoring systems for detection of symptoms and indicators in order to counter harmful medical conditions while they are innocuous. The successful delivery of data whether normal or critical from the patient to his medical practitioner is still a tedious task. Various attempts at designing suitable protocols for WBANs have been made by researchers at different network layers. In this work, we have tried to present an overview of the working methodology of WBAN field, its applications, and various routing protocols designed for WBANs. What should be a suitable number of nodes to be deployed on a human body is still a challenging issue. We have considered three popular routing schemes of WBAN and presented an analysis with varying node deployments to judge their performance. The three schemes considered are SIMPLE, LAEEBA, and EENMBAN.

Keywords

Energy-efficient WBAN Throughput Packet delivery ratio 

References

  1. 1.
    Heinzelman, W. R., Chandrakasan, A., & Balakrishnan, H. (2000). Energy-efficient communication protocol for wireless microsensor networks. In System Sciences, 2000. Proceedings of the 33rd Annual Hawaii International Conference on (p. 10). Piscataway, NJ: IEEE.Google Scholar
  2. 2.
    Khan, F., Bashir, F., & Nakagawa, K. (2012). Dual head clustering scheme in networks. In Emerging Technologies (ICET), 2012 International Conference on (pp. 1–5). Piscataway, NJ: IEEE.Google Scholar
  3. 3.
    Ari, A. A. A., Gueroui, A., Labraoui, N., & Yenke, B. O. (2015). Concepts and evolution of research in the field of wireless sensor networks. arXiv preprint arXiv:1502.03561.Google Scholar
  4. 4.
    Jan, M. A., Jan, S. R. U., Alam, M., Akhunzada, A., & Rahman, I. U. (2018). A comprehensive analysis of congestion control protocols in wireless sensor networks. Mobile Networks and Applications, 23, 1–13.CrossRefGoogle Scholar
  5. 5.
    Sadiq, N., Shah, S. W., Ahmed, S., & Siddiqui, M. M. (2016). Towards an energy-efficient and throughput aware scheme for BANs. In 2nd International Conference on Emerging Trends in Engineering, Management and Sciences (ICETEMS-2016). Google Scholar
  6. 6.
    Jan, M. A., Khan, F., Alam, M., & Usman, M. (2017). A payload-based mutual authentication scheme for Internet of Things. Future Generation Computer Systems. https://doi.org/10.1016/j.future.2017.08.035 CrossRefGoogle Scholar
  7. 7.
    Khan, F., ur Rehman, A., Usman, M., Tan, Z., & Puthal, D. (2018). Performance of cognitive radio sensor networks using hybrid automatic repeat request: Stop-and-wait. Mobile Networks and Applications, 23, 1–10.  https://doi.org/10.1007/s11036-018-1020-4 CrossRefGoogle Scholar
  8. 8.
    Alam, M., Ferreira, J., Mumtaz, S., Jan, M. A., Rebelo, R., & Fonseca, J. A. (2017). Smart cameras are making our beaches safer: A 5G-envisioned distributed architecture for safe, connected coastal areas. IEEE Vehicular Technology Magazine, 12(4), 50–59.CrossRefGoogle Scholar
  9. 9.
    Wang, P., Hou, H., He, X., Wang, C., Xu, T., & Li, Y. (2015). Survey on application of wireless sensor network in smart grid. Procedia Computer Science, 52, 1212–1217.CrossRefGoogle Scholar
  10. 10.
    Khan, F. (2014). Secure communication and routing architecture in wireless sensor networks. In 2014 IEEE 3rd Global Conference on Consumer Electronics (GCCE) (pp. 647–650). Piscataway, NJ: IEEE.Google Scholar
  11. 11.
    Alam, M., Trapps, P., Mumtaz, S., & Rodriguez, J. (2016). Context-aware cooperative testbed for energy analysis in beyond 4G networks. Telecommunication Systems, 64(2), 225–244.  https://doi.org/10.1007/s11235-016-0171-5 CrossRefGoogle Scholar
  12. 12.
    Braem, B., Latre, B., Moerman, I., Blondia, C., Reusens, E., Joseph, W., Martens, L., & Demeester, P. (2007). The need for cooperation and relaying in short-range high path loss sensor networks. In Sensor Technologies and Applications, 2007. SensorComm 2007. International Conference on (pp. 566–571). Piscataway, NJ: IEEE.CrossRefGoogle Scholar
  13. 13.
    Jan, M., Nanda, P., Usman, M., & He, X. (2017). PAWN: A payload-based mutual authentication scheme for wireless sensor networks. Concurrency and Computation: Practice and Experience, 29(17), e3986.CrossRefGoogle Scholar
  14. 14.
    Alam, M., Albano, M., Radwan, A., & Rodriguez, J. (2013). CANDi: Context-aware node discovery for short-range cooperation. Transactions on Emerging Telecommunications Technologies, 26(5), 861–875.  https://doi.org/10.1002/ett.2763 CrossRefGoogle Scholar
  15. 15.
    Chen, B., Varkey, J. P., Pompili, D., Li, J. K. J., & Marsic, I. (2010). Patient vital signs monitoring using wireless body area networks. In Bioengineering Conference, Proceedings of the 2010 IEEE 36th Annual Northeast (pp. 1–2). Piscataway, NJ: IEEE.Google Scholar
  16. 16.
    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.CrossRefGoogle Scholar
  17. 17.
    Nadeem, Q., Javaid, N., Mohammad, S. N., Khan, M. Y., Sarfraz, S., & Gull, M. (2013). Simple: Stable increased-throughput multi-hop protocol for link efficiency in wireless body area networks. In Broadband and Wireless Computing, Communication and Applications (BWCCA), 2013 Eighth International Conference on (pp. 221–226). Piscataway, NJ: IEEE.Google Scholar
  18. 18.
    Ahmed, S., Javaid, N., Akbar, M., Iqbal, A., Khan, Z. A., & Qasim, U. (2014). LAEEBA: Link aware and energy efficient scheme for body area networks. In Advanced Information Networking and Applications (AINA), 2014 IEEE 28th International Conference on (pp. 435–440). Piscataway, NJ: IEEE.Google Scholar
  19. 19.
    Ahmed, S., Javaid, N., Yousaf, S., Ahmad, A., Sandhu, M. M., Imran, M., Khan, Z. A., & Alrajeh, N. (2015). Co-LAEEBA: Cooperative link aware and energy efficient protocol for wireless body area networks. Computers in Human Behavior, 51, 1205–1215.CrossRefGoogle Scholar
  20. 20.
    Jan, M. A., Nanda, P., He, X., & Liu, R. P. (2013, November). Enhancing lifetime and quality of data in cluster-based hierarchical routing protocol for wireless sensor network. In High Performance Computing and Communications & 2013 IEEE International Conference on Embedded and Ubiquitous Computing (HPCC_EUC), 2013 IEEE 10th International Conference on (pp. 1400–1407). Piscataway, NJ: IEEE.Google Scholar
  21. 21.
    Javaid, N., Qureshi, T. N., Khan, A. H., Iqbal, A., Akhtar, E., & Ishfaq, M. (2013). EDDEEC: Enhanced developed distributed energy-efficient clustering for heterogeneous wireless sensor networks. Procedia Computer Science, 19, 914–919.CrossRefGoogle Scholar
  22. 22.
    Abbasi, A. A., & Younis, M. (2007). A survey on clustering algorithms for wireless sensor networks. Computer Communications, 30(14), 2826–2841.CrossRefGoogle Scholar
  23. 23.
    He, D., Chen, C., Chan, S., Jiajun, B., & Zhang, P. (2013). Secure and lightweight network admission and transmission protocol for body sensor networks. IEEE Journal of Biomedical and Health Informatics, 17(3), 664–674.CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Sheeraz Ahmed
    • 1
    • 2
    Email author
  • Nouman Sadiq
    • 1
  • Kamran Sadiq
    • 1
  • Nadeem Javaid
    • 3
  • M. Ali Taqi
    • 1
    • 4
  1. 1.Career Dynamics Research CentrePeshawarPakistan
  2. 2.Iqra National UniversityPeshwarPakistan
  3. 3.COMSATS Institute of Information TechnologyIslamabadPakistan
  4. 4.Gomal UniversityDera Ismail KhanPakistan

Personalised recommendations