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Enhanced Life Time Improvement for Wireless Body Sensor Networks using Optimal Clustering and Advanced Path Selection Protocol

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Abstract

The medical enhancements have been improved to increase the life span of mankind. High penetration of Wireless Sensor Network in medical field helped the doctors to diagnose the patience in accurate manner and prescribe the medicines accordingly. In this modern Era, many people have permanent implant like face maker and it is life threatening to keep changing this body enhancement and it is need to have a system in place to increase the functionality of the Wireless Body Sensors. The important parameter which drags the battery energy and reduces its life span is path loss, and transmission loss. This paper proposes enhanced life time improvement for wireless body sensor networks using optimal clustering and advanced path selection protocol in short Energy Proficient Reliable Multi-hop Routing protocol. The EPMR designed in two stages, the first stage start with the collection of data from all body sensors is done through optimal clustering technique based Modified Conditional Spider Optimization (M-CSO) which avoids continuous individual transmission of data by the sensing nodes to base station in multi- hop distance (this stage the transmission loss is eliminated or reduced) hence the protocol concentrate to reduce transmission losses and the second stage implements the discovery of distance is done through by deploying Modified Flower Bee Algorithm (M-FBA), this stage the protocol finds best suitable and shortest next node to transmit the data. The finding of this paper is simulated using Math lab Simulink and verified through Network Simulator – 2 (NS-2) tools for validation and real time implementation of the results. The result obtained by this proposed method suggests that it has enhanced the sensor life term in many folds in comparisons with existing methodologies.

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References

  1. Ashok, R., & Agrawal, D. (2003). Computing practices - Next-generation wearable networks. Computer, 36(11), 31–39.

    Article  Google Scholar 

  2. Patel, M., & Wang, J. (2010). Applications, challenges, and prospective in emerging body area networking technologies. IEEE Wireless Communication, 17(1), 80–88.

    Article  Google Scholar 

  3. Su, H., & Zhang, X. (2009). Battery-dynamics driven tdma mac protocols for wireless body-area monitoring networks in healthcare applications. IEEE Journal Select Areas Communication, 27(4), 424–434.

    Article  Google Scholar 

  4. Manfredi, S. (2014). Congestion control for differentiated healthcare service delivery in emerging heterogeneous wireless body area networks. IEEE Wireless Communication, 21(2), 81–90.

    Article  Google Scholar 

  5. He, Y., Zhu, W., & Guan, L. (2011). Optimal resource allocation for pervasive health monitoring systems with body sensor networks. IEEE Transactions on Mobile Computing, 10(11), 1558–1575.

    Article  Google Scholar 

  6. Ghasemzadeh, H., Loseu, V., Ostadabbas, S., & Jafari, R. (2010). Burst communication by means of buffer allocation in body sensor networks: Exploiting signal processing to reduce the number of transmissions. IEEE Journal Select Areas Communication, 28(7), 1073–1082.

    Article  Google Scholar 

  7. Zhang, X., Jiang, H., Zhang, L., Zhang, C., Wang, Z., & Chen, X. (2010). An Energy-efficient ASIC for wireless body sensor networks in medical applications. IEEE Transactions on Biomedical Circuits and Systems, 4(1), 11–18.

    Article  Google Scholar 

  8. Rebeiz, E., Caire, G., & Molisch, A. (2012). Energy-delay tradeoff and dynamic sleep switching for bluetooth-like body-area sensor networks. IEEE Transactions on Communications, 60(9), 2733–2746.

    Article  Google Scholar 

  9. Robles, T., Kadelka, A., Velayos, H., Lappetelainen, A., Kassler, A., Hui Li, D., Mandato, J. Ojala., & Wegmann, B. (2001). QoS support for an all IP system beyond 3G. IEEE Communication Magazine, 39(8), 64–72.

    Article  Google Scholar 

  10. Thotahewa, K., Khan, J., & Yuce, M. (2014). Power efficient ultra wide band based wireless body area networks with narrowband feedback path. IEEE Transactions on Mobile Computing, 13(8), 1829–1842.

    Article  Google Scholar 

  11. Ghosh, A., Halder, A., & Dhar, A. (2012). A Variable RF carrier modulation scheme for ultralow power wireless body-Area Network. IEEE Systems Journal, 6(2), 305–316.

    Article  Google Scholar 

  12. Abouei, J., Brown, J., Plataniotis, K., & Pasupathy, S. (2011). Energy efficiency and reliability in wireless biomedical implant Systems. IEEE Transactions on Information Technology in Biomedicine, 15(3), 456–466.

    Article  Google Scholar 

  13. Chang, J., & Ju, P. (2014). An energy-saving routing architecture with a uniform clustering algorithm for wireless body sensor networks. Future Generation Computer Systems, 35, 128–140.

    Article  MathSciNet  Google Scholar 

  14. Bader, A., Abed-Meraim, K., & Alouini, M. (2012). An efficient multi-carrier position-based packet forwarding protocol for wireless Sensor networks. IEEE Transactions on Wireless Communications, 11(1), 305–315.

    Article  Google Scholar 

  15. Sharma, S., & Jena, S. (2015). Cluster based multipath routing protocol for wireless sensor networks. ACM SIGCOMM Computer Communication Review, 45(2), 14–20.

    Article  Google Scholar 

  16. S. Babaie, Ahmad Khadem Zadeh, Mehdi Golsorkhtabar Amiri, (2010). "The New Clustering Algorithm with Cluster Members bounds for energy dissipation avoidance in wireless sensor network", 2010 International Conference On Computer Design and Applications.

  17. Elhabyan, R., & Yagoub, M. (2015). Two-tier particle swarm optimization protocol for clustering and routing in wireless sensor network. Journal of Network and Computer Applications, 52, 116–128.

    Article  Google Scholar 

  18. Du, T., Qu, S., Liu, F., & Wang, Q. (2015). An energy efficiency semi-static routing algorithm for WSNs based on HAC clustering method. Information Fusion, 21, 18–29.

    Article  Google Scholar 

  19. Mahajan, S., Malhotra, J., & Sharma, S. (2014). An energy balanced QoS based cluster head selection strategy for WSN. Egyptian Informatics Journal, 15(3), 189–199.

    Article  Google Scholar 

  20. M. Handy, M. Haase, D. Timmermann, "Low energy adaptive clustering hierarchy with deterministic cluster-head selection", 4th International Workshop on Mobile and Wireless Communications Network.

  21. Ren, J., Zhang, Y., Zhang, K., & Shen, X. (2016). Adaptive and Channel-Aware detection of selective forwarding attacks in wireless sensor networks. IEEE Transactions on Wireless Communications, 15(5), 3718–3731. https://doi.org/10.1109/twc.2016.2526601

    Article  Google Scholar 

  22. Hacioglu, G., Kand, V. F. A., & Sesli, E. (2016). Multi objective clustering for wireless sensor networks. Expert Systems with Applications, 59, 86–100. https://doi.org/10.1016/j.eswa.2016.04.016

    Article  Google Scholar 

  23. Anwar, A., & Sridharan, D. (2018). A predictive routing algorithm for wbsn based on kalman filter iterations. IEEE Sensors Journal. https://doi.org/10.1109/jsen.2018.2847049

    Article  Google Scholar 

  24. Afsana, F., Asif-Ur-Rahman, M., Ahmed, M. R., Mahmud, M., & Kaiser, M. S. (2018). An energy conserving routing scheme for wireless body sensor nanonetwork communication. IEEE Access, 6, 9186–9200. https://doi.org/10.1109/access.2018.2789437C

    Article  Google Scholar 

  25. DelBello, C., Raihan, K., & Zhang, T. (2015). Reducing energy consumption of mobile phones during data transmission and encryption for wireless body area network applications. Security and Communication Networks, 8(17), 2973–2980. https://doi.org/10.1002/sec.1223

    Article  Google Scholar 

  26. Chen, D.-R., Hsu, C.-C., Chen, M.-Y., & Guo, C.-F. (2018). A power-aware 2-covered path routing for wireless body area networks with variable transmission ranges. Journal of Parallel and Distributed Computing, 118, 379–397. https://doi.org/10.1016/j.jpdc.2017.08.006

    Article  Google Scholar 

  27. Kaur, N., & Singh, S. (2017). Optimized cost effective and energy efficient routing protocol for wireless body area networks. Ad Hoc Networks, 61, 65–84. https://doi.org/10.1016/j.adhoc.2017.03.008

    Article  Google Scholar 

  28. Khan, R., Mohammadani, K., Soomro, A., Hussain, J., Khan, S., Arain, T., & Zafar, H. (2018). An energy efficient routing protocol for wireless body area sensor networks. Wireless Personal Communications, 99(4), 1443–1454.

    Article  Google Scholar 

  29. Sangeetha Priya, N., Sasikala, R., Alavandar, S., & Bharathi, L. (2018). Security aware trusted cluster based routing protocol for wireless body sensor networks. Wireless Personal Communications, 102(4), 3393–3411.

    Article  Google Scholar 

  30. Bhangwar, A., Kumar, P., Ahmed, A., & Channa, M. (2017). Trust and thermal aware routing protocol (ttrp) for wireless body area networks. Wireless Personal Communications, 97(1), 349–364.

    Article  Google Scholar 

  31. Rangi, S., Vashist, S., & Chakarvarti, Prof(Dr)SK. . (2016). A review on wireless body area network (wban) for health monitoring system: Implementation protocols. Communications on Applied Electronics., 4, 16–20. https://doi.org/10.5120/cae2016652130

    Article  Google Scholar 

  32. Raja Basha, A., & Yaashuwanth, C. (2019). Optimal partial aggregation based energy delay compromise technique for wireless sensor network. IETE Journal of Research, 65(6), 855–871. https://doi.org/10.1080/03772063.2018.1464966

    Article  Google Scholar 

  33. Basha, A. R., & Yaashuwanth, C. (2020). Double secure optimal partial aggregation using trust inference and hybrid syncryption algorithm for wireless sensor networks. Journal of Computational and Theoretical Nanoscience, 15(2), 423–436. https://doi.org/10.1166/jctn.2018.7106

    Article  Google Scholar 

  34. Zuhra, F. T., Bakar, K. A., Ahmed, A., & Tunio, M. A. (2017). Routing protocols in wireless body sensor networks: A comprehensive survey. Journal of Network and Computer Applications, 99, 73–97. https://doi.org/10.1016/j.jnca.2017.10.002

    Article  Google Scholar 

  35. Ullah, F., Abdullah, A., Kaiwartya, O., & Arshad, M. (2017). Traffic priority-aware adaptive slot allocation for medium access control protocol in wireless body area network. Computers, 6(1), 9. https://doi.org/10.3390/computers6010009

    Article  Google Scholar 

  36. Razzaque, M. A., Hira, M. T., & Dira, M. (2017). QoS in body area networks. ACM Transactions on Sensor Networks, 13(3), 1–46. https://doi.org/10.1145/3085580

    Article  Google Scholar 

  37. Culpepper, B. J., Dung, L., & Moh, M. (2004). Design and analysis of Hybrid Indirect transmissions (HIT) for data gathering in wireless micro sensor networks. ACM SIGMOBILE Mobile Computing and Communications Review., 8, 61–83.

    Article  Google Scholar 

  38. Sharma, S., Agarwal, P., & Jena, S. K. (2013). Energy Aware Multipath Routing Protocol for Wireless Sensor Networks. In Nabendu Chaki, Natarajan Meghanathan, & Dhinaharan Nagamalai (Eds.), Computer Networks & Communications (NetCom) (pp. 753–60). New York: Springer.

    Chapter  Google Scholar 

  39. Coello, C. A. (2000). An updated survey of GA-based multiobjective optimization techniques. ACM Computing Surveys (CSUR), 32, 109–143.

    Article  Google Scholar 

  40. Esmaeili, H., & Minaei Bidgoli, B. (2018). EMRP: Evolutionary-based multi-hop routing protocol for wireless body area networks. AEU - International Journal of Electronics and Communications, 93, 63–74.

    Article  Google Scholar 

Download references

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  1. Department of Electronics and Communication Engineering, Audisankara College of Engineering and Technology, NH - 5 Bypass Road, Aravinda Nagar, 524101, Nellore, Gudur, A.P, India

    Adam Raja Basha & Hariprasath Manoharan

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Correspondence to Adam Raja Basha.

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Basha, A.R., Manoharan, H. Enhanced Life Time Improvement for Wireless Body Sensor Networks using Optimal Clustering and Advanced Path Selection Protocol. Wireless Pers Commun 119, 2123–2146 (2021). https://doi.org/10.1007/s11277-021-08322-5

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