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ECMR: Energy Constrained Mobile Routing for Wireless Sensor Networks

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Abstract

Mobile wireless sensor network (MWSN) has eventual applications in various areas such as health care monitoring, flood and fire detection, wildlife monitoring etc. MWSNs have fascinated much attentiveness from patrons in recent years due to their applications in various fields. MWSNs are resource restraints and demand performance investigation by numerous node mobility patterns. Generally, in MWSN, the routing algorithms have been investigated for predefined mobility. But for real-time applications, it is essential to develop an effective routing algorithm and study the effects of various mobility patterns on routing strategies to give effective outcomes. Therefore, keeping in view of the above issue, we proposed an Energy Constrained Mobile Routing (ECMR) in this paper. Simulations have been performed in MATLAB on diverse parameters to check the efficiency of ECMR and other existing routing protocols. Simulation results show that ECMR gives better performance than the Position-Based Routing (PBR) protocol, which comprises Mobility Aware Routing (MAR) and Geographic Robust Clustering (GRC). ECMR has also shown better performance than Non-Position Based Routing (N-PBR) protocols comprising Distributed Efficient Clustering Approach (DECA) and Distributed Efficient Multi-hop Clustering (DEMC). ECMR reduces the percentage of packet loss 10–12%, increases packet delivery ratio 11–13%, minimizes average end-to-end delay 13–15%, enhances throughput 12–14%, reduces overhead 11–12%, minimizes energy consumption 16–18%, and prolongs network lifetime 15–17% on the mobility of sensor nodes. ECMR performs better with Random Waypoint Mobility (RWPM) model than Pathway mobility (PM) and Random Walk Mobility (RWM) model.

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References

  1. Hayes, T., & Ali, F. H. (2016). Robust Ad-hoc sensor Routing (RASeR) protocol for mobile wireless sensor networks. Ad hoc Networks, 50, 128–144.

    Article  Google Scholar 

  2. Bensaleh, M. S., Saida, R., Kacem, Y. H., et al. (2020). Wireless sensor network design methodologies: A survey. Journal of Sensors, 2020, 1–13.

    Article  Google Scholar 

  3. Gao, Y., Ao, H., Feng, Z., et al. (2018). Mobile Network Security and Privacy in WSN. Procedia Computer Science, 129, 324–330.

    Article  Google Scholar 

  4. Chaochen, X., Xiaoheng, T., Balginbek, T., et al. (2018). Research of resource allocation technology based on MIMO ultra density heterogeneous network for 5G. Procedia Computer Science, 131, 1039–1047.

    Article  Google Scholar 

  5. Fu, Y., Lien, T., & Lin, F. (2018). Application association and load balancing to enhance energy efficiency in heterogeneous wireless networks. Computers & Electrical Engineering, 68, 348–365.

    Article  Google Scholar 

  6. Padmaja, P., & Marutheswar, G. V. (2018). Energy efficient data aggregation in wireless sensor networks. Procedia Computer Science, 5, 388–396.

    Google Scholar 

  7. Kaur, S., & Mahajan, R. (2018). Hybrid meta-heuristic optimization based energy efficient protocol for wireless sensor networks. Egyptian Informatics Journal, 7, 386–398.

    Google Scholar 

  8. Zareei, M., Islam, A., & Rosales, C. (2018). Mobility-aware medium access control protocols for wireless sensor networks: A survey. Journal of Network and Computer Applications, 104, 21–27.

    Article  Google Scholar 

  9. Shahraki, A., Taherkordi, A., Haugen, O., et al. (2020). Clustering objectives in wireless sensor networks: A survey and research direction analysis. Computer Networks, 180, 1–75.

    Article  Google Scholar 

  10. Ferandis, T., Silvestre, J., Santonja, S., et al. (2018). Deploy&Forget wireless sensor networks for itinerant applications. Computer Standards & Interfaces, 56, 27–40.

    Article  Google Scholar 

  11. Nagarju, S., Gudino, L. J., Tripathi, N., et al. (2018). Mobility assisted localization for mission critical wireless sensor network applicationsusing hybrid area exploration approach. JKSU-CIS, 6, 79–85.

    Google Scholar 

  12. Asad, M., Nianmin, Y., & Aslam, M. (2018). Spiral mobility based on optimized clustering for optimal data extraction in WSNs. MDPI, 35, 6–36.

    Google Scholar 

  13. Ketshabetswe, L. K., Zungeru, A. M., Mangwala, M., et al. (2019). Coomunication protocols for wireless sensor networks: A survey and comparison. Holiyan, 5, 1–43.

    Google Scholar 

  14. Samiha, M. E., Elsherif, M., & Wahed, M. E. (2018). An enhancement approach for reducing the energy consumption in wireless sensor networks. JKSU-CIS, 30, 259–267.

    Google Scholar 

  15. Alkindi, Z., Alzeidi, N., Arafehand, B., & Touzene, A. (2018). Performance evaluation of grid based routing for under water wireless sensor networks under different mobility models. International Journal of Wireless & Mobile Networks (IJWMN), 10(1), 13–15.

    Article  Google Scholar 

  16. Huanga, Y., Wangb, L., Hou, Y., et al. (2018). A prototype IOT based wireless sensor network for traffic information monitoring. International Journal of Pavement Research and Technology, 11(2), 146–152.

    Article  Google Scholar 

  17. Almesaeed, R., & Jedidi, A. (2021). Dynamic directional routing for mobile wireless sensor networks. Ad Hoc Networks, 110, 1–8.

    Article  Google Scholar 

  18. Zagrouba, R., & Kardi, A. (2021). Comparative study of energy efficient routing techniques in wireless sensor networks. Journal of Information, 12(42), 1–28.

    Google Scholar 

  19. Muhtadi, J. A., Qiang, M., Zeb, K., et al. (2018). A critical analysis of mobility management related issues of wireless sensor networks in cyber physical systems. SAICPS, 8, 16363–16376.

    Google Scholar 

  20. Echoukairi, H., Kada, A., Bourgba, K., et al. (2017). Effect of mobility models on performance of novel centralized clustering approach based on k-means for wireless sensor networks. IJAER, 12(10), 2575–2580.

    Google Scholar 

  21. Kaur, U., & Sharma, S. (2017). Parmetric analysis of energy aware clustering and routing protocols used in WSN. International Journal of Advanced Research in Computer Science, 8(9), 342–350.

    Google Scholar 

  22. Shantha, R., Kumari, S., Chitra, A., et al. (2016). Efficient -2 level energy heterogeneity clustering protocols for wireless sensor networks. Indian Journal of Science and Technology, 9(3), 1–6.

    Google Scholar 

  23. Ramluckun, N., & Bassoo, V. (2018). Energy-efficient chain-cluster based intelligent routing technique for wireless sensor networks. Applied Computing and Informatics, 7, 1–12.

    Google Scholar 

  24. SureshKumar, K., & Vimala, P. (2021). Energy efficient routing protocol using exponentially-ant lion whale optimization algorithm in wireless sensor networks. Computer Networks, 197, 1–12.

    Article  Google Scholar 

  25. Lakhotia, J., & Kumar, R. (2014). Fault tolerant and mobility aware routing protocol for mobile wireless sensor network. In 2014 International Conference on Control, Instrumentation, Communication and Computational Technologies (ICCICCT) (pp. 584-590). IEEE

  26. Maheshwari, P., Sharma, A. K., & Verma, K. (2021). Energy efficient cluster based routing protocol for WSN using butterfly optimization algorithm and ant colony optimization. Ad Hoc Networks, 110, 1–52.

    Article  Google Scholar 

  27. Agbehadji, I. E., Millham, R. C., Abayomi, A., et al. (2021). Clustering algorithm based on nature-inspired approach for energy optimization in heterogeneous wireless sensor network. Applied Soft Computing, 104, 1–15.

    Article  Google Scholar 

  28. Janabi, S. A., Shourbaji, I. A., Shojafar, M., et al. (2017). Survey of main challenges (security and privacy) in wireless body area networks for healthcare applications. Egyptian Informatics Journal, 18(2), 113–122.

    Article  Google Scholar 

  29. Kumar, S., & Singh, A. K. (2021). A localized algorithm for clustering in cognitive radio networks. Journal of King Saud University-Computer and Information Sciences, 33(5), 600–607.

    Article  Google Scholar 

  30. Kalaivaani, P. T., & Krishnamoorthy, R. (2018). Performance analysis of various hierarchical routing protocols using spatial correlation. Journal of Measurement. https://doi.org/10.1016/j.measurement.2018.11.084

    Article  Google Scholar 

  31. Van Khoa, V., & Takayama, S. (2018). Wireless sensor network in landslide monitoring system with remote data management. Journal of Measurement, 118, 214–229.

    Article  Google Scholar 

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Authors and Affiliations

  1. MJP Rohilkhand University, Bareilly, Uttar Pradesh, India

    Vinay Rishiwal

  2. National Institute of Fashion Technology, Patna, Bihar, India

    Omkar Singh

  3. Bareilly College, Bareilly, Uttrar Pradesh, India

    Mano Yadav

Authors
  1. Vinay Rishiwal
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  2. Omkar Singh
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  3. Mano Yadav
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Correspondence to Omkar Singh.

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Appendix 1

Appendix 1

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Fig. 23
figure 23

Classification of Mobility Models

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Rishiwal, V., Singh, O. & Yadav, M. ECMR: Energy Constrained Mobile Routing for Wireless Sensor Networks. Wireless Pers Commun 124, 2939–2964 (2022). https://doi.org/10.1007/s11277-022-09497-1

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  • DOI: https://doi.org/10.1007/s11277-022-09497-1

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