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A novel algorithm for the development of a multipath protocol for routing and energy efficient in IoT with varying density

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Abstract

Data transmission from sensor nodes is the biggest problem for IoT networks. Overusing communication power shortens node lifespans. Thus, network issues including QoS, security, network heterogeneity, congestion avoidance, reliable routing, and energy savings must be addressed. Routing protocols are essential for delivering data between organizations. Information gathering and consolidation require data aggregation to minimize traffic congestion, operating expenses, energy usage, and network lifespan. IoT data aggregation makes route planning dependable, energy-efficient, and difficult. Disjoint & Scalable Multipath Routing (D &SMR) is a new routing system developed using NS2 simulation. The method estimates delivery success using decision trees and neural networks. We evaluate characteristics such as (D &SMR) routing scheme predictability, node popularity, power consumption, speed, and location while training the model. Simulation results show that (D &SMR) outperforms a reliable routing system in terms of delivery success, lost messages, overhead, and hop count. The proposed hybrid routing method involves cluster construction and intra- and inter-cluster routing. The study found that (D &SMR) beats previous research in network resilience, packet transmission efficiency, end-to-end latency, and energy usage.

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The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.

References

  1. Ghamari, M., Janko, B., Sherratt, R. S., Harwin, W., Piechockic, R., & Soltanpur, C. (2016). A survey on wireless body area networks for ehealthcare systems in residential environments. Sensors, 16(6), 831.

    Article  Google Scholar 

  2. Crosby, G. V., Ghosh, T., Murimi, R., & Chin, C. A. (2012). Wireless body area networks for healthcare: A survey. International Journal of Ad Hoc, Sensor & Ubiquitous Computing, 3(3), 1.

    Article  Google Scholar 

  3. Arafat, M. Y., & Moh, S. (2022). JRCS: Joint routing and charging strategy for logistics drones. IEEE Internet of Things Journal, 9(21), 21751–21764.

    Article  Google Scholar 

  4. Mu, J., Wei, Y., Ma, H., & Li, Y. (2020). Spectrum allocation scheme for intelligent partition based on machine learning for inter-WBAN interference. IEEE Wireless Communications, 27(5), 32–37.

    Article  Google Scholar 

  5. Al-Turjman, F. (2017). Energy-aware data delivery framework for safety-oriented mobile IoT. IEEE Sensors Journal, 18(1), 470–478.

    Article  Google Scholar 

  6. Aledhari, M., Razzak, R., Qolomany, B., Al-Fuqaha, A., & Saeed, F. (2022). Biomedical IoT: Enabling technologies, architectural elements, challenges, and future directions. IEEE Access, 10, 31306–31339.

    Article  Google Scholar 

  7. Dian, F. J., Vahidnia, R., & Rahmati, A. (2020). Wearables and the internet of things (IoT), applications, opportunities, and challenges: A survey. IEEE Access, 8, 69200–69211.

    Article  Google Scholar 

  8. Barakah, D.M., & Ammad-Uddin, M (2012). A survey of challenges and applications of wireless body area network (WBAN) and role of a virtual doctor server in existing architecture. In 2012 Third international conference on intelligent systems modelling and simulation, IEEE. pp. 214–219.

  9. Qu, Y., Zheng, G., Ma, H., Wang, X., Ji, B., & Wu, H. (2019). A survey of routing protocols in WBAN for healthcare applications. Sensors, 19(7), 1638.

    Article  Google Scholar 

  10. Li, S., Kim, J. G., Han, D. H., & Lee, K. S. (2019). A survey of energy-efficient communication protocols with QoS guarantees in wireless multimedia sensor networks. Sensors, 19(1), 199.

    Article  Google Scholar 

  11. Rani, S., Talwar, R., Malhotra, J., Ahmed, S. H., Sarkar, M., & Song, H. (2015). A novel scheme for an energy efficient internet of things based on wireless sensor networks. Sensors, 15(11), 28603–28626. https://doi.org/10.3390/s151128603

    Article  Google Scholar 

  12. Yadav, R. N., Misra, R., & Saini, D. (2018). Energy aware cluster based routing protocol over distributed cognitive radio sensor network. Computer Communications, 129, 54–66. https://doi.org/10.1016/j.comcom.2018.07.020

    Article  Google Scholar 

  13. Cengiz, K., & Dag, T. (2017). Energy aware multi-hop routing protocol for WSNs. IEEE Access, 6, 2622–2633.

    Article  Google Scholar 

  14. **ao, K., Wang, R., Deng, H., Zhang, L., & Yang, C. (2019). Energy-aware scheduling for information fusion in wireless sensor network surveillance. Information Fusion, 48, 95–106.

    Article  Google Scholar 

  15. Altowaijri, S. M. (2022). Efficient next-hop selection in multi-hop routing for IoT enabled wireless sensor networks. Future Internet, 14(2), 35.

    Article  Google Scholar 

  16. Moussa, N., Hamidi-Alaoui, Z., & El Belrhiti El Alaoui, A. (2020). ECRP: An energy-aware cluster-based routing protocol for wireless sensor networks. Wireless Networks, 26, 2915–2928.

    Article  Google Scholar 

  17. Mehmood, A., Mauri, J. L., Noman, M., & Song, H. (2015). Improvement of the wireless sensor network lifetime using leach with vice-cluster head. Ad Hoc and Sensor Wireless Networks, 28(1–2), 1–17.

    Google Scholar 

  18. Shagari, N. M., Idris, M. Y. I., Salleh, R. B., Ahmedy, I., Murtaza, G., & Shehadeh, H. A. (2020). Heterogeneous energy and traffic aware sleep-awake cluster-based routing protocol for wireless sensor network. IEEE Access, 8, 12232–12252.

    Article  Google Scholar 

  19. Salunkhe, S. P., & Patil, H. D. (2016). Delay efficient authenticated anonymous secure routing for MANETs. International Journal of Computer Applications, 148(4).

  20. Sbeiti, M., Goddemeier, N., Behnke, D., & Wietfeld, C. (2015). PASER: Secure and efficient routing approach for airborne mesh networks. IEEE Transactions on Wireless Communications, 15(3), 1950–1964.

    Article  Google Scholar 

  21. Babbitt, T. A., & Szymanski, B. K. (2016). Trust based secure routing in delay tolerant networks. In 2016 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), IEEE. pp. 542–547.

  22. Kardaş, S., Celik, S., Arslan, A., & Levi, A. (2013). An efficient and private RFID authentication protocol supporting ownership transfer. In Lightweight cryptography for security and privacy: Second international workshop, LightSec 2013, Gebze, Turkey, May 6-7, 2013, Revised Selected Papers 2, Springer. pp. 130–141.

  23. Saxena, D., & Patel, P. (2023). Energy-efficient clustering and cooperative routing protocol for wireless body area networks (WBAN). Sādhanā, 48(2), 71.

    Article  Google Scholar 

  24. Lalitha, S., Sundararajan, M., & Karthik, B. (2023). Reliable multi-path route selection strategy based on evidence theory for internet of things enabled networks. Measurement: Sensors, 27, 100795.

    Google Scholar 

  25. Raja Basha, A. (2022). A review on wireless sensor networks: Routing. Wireless Personal Communications, 125(1), 897–937.

    Article  Google Scholar 

  26. Haseeb, K., Saba, T., Rehman, A., Ahmed, Z., Song, H. H., & Wang, H. H. (2022). Trust management with fault-tolerant supervised routing for smart cities using internet of things. IEEE Internet of Things Journal, 9(22), 22608–22617.

    Article  Google Scholar 

  27. Chandnani, N., & Khairnar, C. N. (2022). An analysis of architecture, framework, security and challenging aspects for data aggregation and routing techniques in IoT WSNs. Theoretical Computer Science, 929, 95–113.

    Article  Google Scholar 

  28. Reddy Yeruva, A., Saleh Alomari, E., Rashmi, S., Shrivastava, A., Kathiravan, M., & Chaturvedi, A. (2023). A secure machine learning-based optimal routing in ad hoc networks for classifying and predicting vulnerabilities. Cybernetics and Systems, 1–12.

  29. Vellela, S. S., & Balamanigandan, R. (2023). Optimized clustering routing framework to maintain the optimal energy status in the WSN mobile cloud environment. Multimedia Tools and Applications, 1–20.

  30. Kaythry, P., Kishore, R., & Avinash, E. (2024). Reliability based multistage ARQ for wide area wireless sensor networks. Journal of Engineering Science and Technology, 19(2), 374–389.

    Google Scholar 

  31. Papachary, B., Arya, R., & Dappuri, B. (2024). Power-aware QoS-centric strategy for ultra reliable low latency communication in 5G beyond wireless networks. Cluster Computing, 1–14.

  32. Dasari, R., & Venkatram, N. (2024). Optimizing multichannel path scheduling in cognitive radio Ad HoC networks using differential evolution. Scalable Computing: Practice and Experience, 25(2), 1199–1218.

    Google Scholar 

  33. Rocha, D., Teixeira, G., Vieira, E., Almeida, J., & Ferreira, J. (2023). A modular in-vehicle c-its architecture for sensor data collection, vehicular communications and cloud connectivity. Sensors, 23(3), 1724.

    Article  Google Scholar 

  34. Kaur, P., Kaur, K., Singh, K., Bharany, S., Almazyad, A. S., **ong, G., Mohamed, A. W., Shokouhifar, M., & Werner, F. (2023). Acoustic monitoring in underwater wireless sensor networks using energy-efficient artificial fish swarm-based clustering protocol (EAFSCP).

  35. Wang, H., Li, Y., Zhang, Y., Huang, T., & Jiang, Y. (2023). Arithmetic optimization AOMDV routing protocol for FANETs. Sensors, 23(17), 7550.

    Article  Google Scholar 

  36. Manoharan, J. S. (2023). A metaheuristic approach towards enhancement of network lifetime in wireless sensor networks. KSII Transactions on Internet & Information Systems, 17(4).

  37. Hadwa, S. M., Ghouraba, R. F., Kabbash, I. A., & El-Desouky, S. S. (2023). Assessment of clinical and radiographic efficiency of manual and pediatric rotary file systems in primary root canal preparation: A randomized controlled clinical trial. BMC Oral Health, 23(1), 687.

    Article  Google Scholar 

  38. Ullah, S., Saleem, A., Hassan, N., Muhammad, G., Shin, J., Minhas, Q. -A., & Khan, M. K. (2023). Reliable and delay aware routing protocol for underwater wireless sensor networks. IEEE Access.

  39. Gopi, B., Ramesh, G., & Logeshwaran, J. (2022). The fuzzy logical controller based energy storage and conservation model to achieve maximum energy efficiency in modern 5G communication. ICTACT Journal on Communication Technology, 13(3), 2774–2779.

    Article  Google Scholar 

  40. Sahu, M., Sethi, N., & Das, S. K. (2022). Secure data transmission in wireless sensor networks with secure system for identification of trusted route with node behavior analysis. Revue d’Intelligence Artificielle, 36(2).

  41. Gupta, S. K., & Singh, S. (2022). Survey on energy efficient dynamic sink optimum routing for wireless sensor network and communication technologies. International Journal of Communication Systems, 35(11), 5194.

    Article  Google Scholar 

  42. Abbas, G., Ullah, S., Waqas, M., Abbas, Z. H., & Bilal, M. (2022). A position-based reliable emergency message routing scheme for road safety in VANETs. Computer Networks, 213, 109097.

    Article  Google Scholar 

  43. Valle, M. S., Casabona, A., Sapienza, I., Laudani, L., Vagnini, A., Lanza, S., & Cioni, M. (2022). Use of a single wearable sensor to evaluate the effects of gait and pelvis asymmetries on the components of the timed up and go test, in persons with unilateral lower limb amputation. Sensors, 22(1), 95.

    Article  Google Scholar 

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  1. Faculty Information Technology and Computing, Arab Open University-Kuwait, Alardiya Industrial, 830, 92400, Al-Ardiya, Kuwait

    Radwan S. Abujassar

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Abujassar, R.S. A novel algorithm for the development of a multipath protocol for routing and energy efficient in IoT with varying density. Telecommun Syst (2024). https://doi.org/10.1007/s11235-024-01170-1

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