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Investigate and Study the Best Position of Base Station for WMSNs

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Abstract

Wireless Multimedia Sensor Networks (WMSNs) have been an essential part of our lives, with various applications from disaster assistance to medical services. As a result, the lifetime and energy consumption of WMSNs have become challenging research issues. In the previous decades, a large number of protocols have been established to improve the energy efficiency of WMSNs. One of the proposed solutions is clustering. The cluster head selection criteria, network architecture, and heterogeneity are mostly addressed in these protocols. In this paper, we proposed an Energy-Efficient Multipath Clustering with Load Balancing Routing Protocol for Wireless Multimedia Sensor Networks (EEMCL). In the proposed protocol, the main cluster heads (MCHs) are preselected in each cluster in the network field with more energy than normal sensor nodes. The selection of two secondary cluster heads (SCHs) by the main cluster heads algorithm is used in which nodes have higher energy will be chosen as SCHs. Moreover, inter-cluster multi-hop routing with the help of MCHs can enhance the network lifetime when the sink is located at the corner of the network area. The MATLAB simulation tool is used to investigate the performance of the proposed protocol EEMCL. The results have been shown that the best position of the base station (BS) is at the center of the network area which can prolong the lifetime of sensor nodes, and random distribution of the sensor nodes gives better performance relating to the residual energy and the nodes still alive than static distribution.

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References

  1. Yetgin, H., Cheung, K. T. K., El-Hajjar, M., & Hanzo, L. H. (2017). A survey of network lifetime maximization techniques in wireless sensor networks. IEEE Communications Surveys & Tutorials, 19(2), 828–854.

    Article  Google Scholar 

  2. Elhabyan, R. S. Y., & Yagoub, M. C. E. (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 

  3. Amgoth, T., & Jana, P. K. (2015). Energy-aware routing algorithm for wireless sensor networks. Computers & Electrical Engineering, 41, 357–367.

    Article  Google Scholar 

  4. Al-Junaid, A. F., & Al-Kamali, F. S. (2016). Efficient wireless transmission scheme based on the recent DST-MC-CDMA. Wireless Networks, 22(3), 813–824.

    Article  Google Scholar 

  5. Peng, S., Wang, T., & Low, C. P. (2015). Energy neutral clustering for energy harvesting wireless sensors networks. Ad Hoc Networks, 28, 1–16.

    Article  Google Scholar 

  6. Saranya, V., Shankar, S., & Kanagachidambaresan, G. R. (2018). Energy efficient clustering scheme (EECS) for wireless sensor network with mobile sink. Wireless Personal Communications, 100(4), 1553–1567.

    Article  Google Scholar 

  7. RejinaParvin, J., & Vasanthanayaki, C. (2015). Particle swarm optimization-based clustering by preventing residual nodes in wireless sensor networks. IEEE sensors journal, 15(8), 4264–4274.

    Article  Google Scholar 

  8. Khan, I., Belqasmi, F., Glitho, R., Crespi, N., Morrow, M., & Polakos, P. (2015). Wireless sensor network virtualization: A survey. IEEE Communications Surveys & Tutorials, 18(1), 553–576.

    Article  Google Scholar 

  9. Kuila, P., & Jana, P. K. (2014). Energy efficient clustering and routing algorithms for wireless sensor networks: Particle swarm optimization approach. Engineering Applications of Artificial Intelligence, 33, 127–140.

    Article  Google Scholar 

  10. Gu, X., Jiguo, Yu., Dongxiao, Yu., Wang, G., & Lv, Y. (2014). ECDC: An energy and coverage-aware distributed clustering protocol for wireless sensor networks. Computers & Electrical Engineering, 40(2), 384–398.

    Article  Google Scholar 

  11. Chen, W., & Lea, C.-T. (2016). Oblivious routing in wireless mesh networks. Wireless Networks, 22(7), 2337–2353.

    Article  Google Scholar 

  12. Tyagi, S., & Kumar, N. (2013). A systematic review on clustering and routing techniques based upon LEACH protocol for wireless sensor networks. Journal of Network and Computer Applications, 36(2), 623–645.

    Article  Google Scholar 

  13. Tanwar, S. (2015). Neeraj Kumar, and Joel JPC Rodrigues, “A systematic review on heterogeneous routing protocols for wireless sensor network.” Journal of network and computer applications, 53, 39–56.

    Article  Google Scholar 

  14. Shin, H., Moh, S., Chung, I., & Kang, M. (2015). Equal-size clustering for irregularly deployed wireless sensor networks. Wireless Personal Communications, 82(2), 995–1012.

    Article  Google Scholar 

  15. Baranidharan, B., & Santhi, B. (2016). DUCF: Distributed load balancing unequal clustering in wireless sensor networks using fuzzy approach. Applied Soft Computing, 40, 495–506.

    Article  Google Scholar 

  16. Azharuddin, Md., Kuila, P., & Jana, P. K. (2015). Energy efficient fault tolerant clustering and routing algorithms for wireless sensor networks. Computers & Electrical Engineering, 41, 177–190.

    Article  Google Scholar 

  17. Li, C., Ye, M., Chen, G., & Wu, J. (2005) An energy-efficient unequal clustering mechanism for wireless sensor networks. In IEEE International Conference on Mobile Adhoc and Sensor Systems Conference, pp. 604–612.

  18. Soro, S., & Heinzelman, W. B. (2005). Prolonging the lifetime of wireless sensor networks via unequal clustering. In 19th IEEE international parallel and distributed processing symposium, pp. 236–243.

  19. Chen, G., Li, C., Ye, M., & Jie, Wu. (2009). An unequal cluster-based routing protocol in wireless sensor networks. Wireless Networks, 15(2), 193–207.

    Article  Google Scholar 

  20. Selvi, G. V., & Manoharan, R. (2013). A survey of energy efficient unequal clustering algorithms for wireless sensor networks. International Journal of Computer Applications, 79(1), 2013.

    Google Scholar 

  21. Guiloufi, A. B., Fradj, N. N., & Kachouri, A. (2016). An energy-efficient unequal clustering algorithm using ‘Sierpinski Triangle’for WSNs. Wireless Personal Communications, 88(3), 449–465.

    Article  Google Scholar 

  22. Shokouhifar, M., & Jalali, A. (2017). Optimized sugeno fuzzy clustering algorithm for wireless sensor networks. Engineering applications of artificial intelligence, 60, 16–25.

    Article  Google Scholar 

  23. Logambigai, R., & Kannan, A. (2016). Fuzzy logic based unequal clustering for wireless sensor networks. Wireless Networks, 22(3), 945–957.

    Article  Google Scholar 

  24. Heinzelman, W. R., Chandrakasan, A., & Balakrishnan, B. (2000). Energy-efficient communication protocol for wireless microsensor networks. In Proceedings of the 33rd IEEE annual Hawaii international conference on system sciences, pp. 1–10.

  25. Lee, J.-Y., Jung, K.-D., Moon, S.-J., & Jeong, H.-Y. (2017). Improvement on LEACH Protocol of a wide-area wireless sensor network. Multimedia Tools and Applications, 76(19), 19843–19860.

    Article  Google Scholar 

  26. Balakrishnan, B., & Balachandran, S. (2017). FLECH: Fuzzy logic-based energy efficient clustering hierarchy for nonuniform wireless sensor networks. Wireless Communications and Mobile Computing, 2017, 1–14.

    Article  Google Scholar 

  27. Liu, Y., Qiong, Wu., Zhao, T., Tie, Y., Bai, F., & Jin, M. (2019). An improved energy-efficient routing protocol for wireless sensor networks. Sensors, 19(20), 1–20.

    Article  Google Scholar 

  28. Farooq, M. O., Dogar, A. B., & Shah, G. A. (2010). MR-LEACH: Multi-hop routing with low energy adaptive clustering hierarchy. In 4th international conference on sensor technologies and applications, pp. 262–268.

  29. Cengiz, K., & Dag, T. (2016). Improving energy-efficiency of WSNs through LEFCA. International Journal of Distributed Sensor Networks, 12(8), 1–12.

    Article  Google Scholar 

  30. Bozorgi, S. M., & Bidgoli, A. M. (2019). HEEC: A hybrid unequal energy efficient clustering for wireless sensor networks. Wireless Networks, 25(8), 4751–4772.

    Article  Google Scholar 

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The authors did not receive support from any organization for the submitted work.

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The first author “Madyen Mohammed Saleem” contributed to writing and programming the proposed protocol and obtaining the results. The second author “Salah Abdulghani Alabady” (the student's supervisor) contributed to writing, correcting and revising the language, giving appropriate directions on how to write, and analyzing and discussing the results.

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Correspondence to Salah Abdulghani Alabady.

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Saleem, M.M., Alabady, S.A. Investigate and Study the Best Position of Base Station for WMSNs. Wireless Pers Commun 134, 411–444 (2024). https://doi.org/10.1007/s11277-024-10915-9

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