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Lightning-Based Lion Optimization Algorithm for Monitoring the Pipelines Using Linear Wireless Sensor Network

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Abstract

Monitoring of pipelines carrying oil, gas and water is necessary to avoid the wastage of these natural resources. Linear Wireless Sensor Network (LWSN) is one of the best ways to monitor these pipelines efficiently. In LWSN, the positioning of nodes and the routing scheme can be used to avoid the losses occur during transportation of these resources to their corresponding destinations. This paper modifies the Lion Optimization Algorithm by using the lightning procedure of cloud for defining the position of sensor nodes while for routing jump and redirect routing scheme is used. In this algorithm, the lions travel from one location to the other as the light moves from cloud towards the ground. The algorithm proves its significance by showing significant improvement while comparing its performance with four existing algorithms including Lion Optimization Algorithm, Genetic Algorithm, Ant Colony Optimization and without optimization. The performance parameters considered during simulation are delay, throughput and lifetime.

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References

  1. Varshney, S., Kumar, C., & Swaroop, A. (2015). A comparative study of hierarchical routing protocols in wireless sensor networks.” In 2015 2nd international conference on computing for sustainable global development (INDIACom). IEEE.

  2. Jawhar, I., Mohamed, N., & Agrawal, D. P. (2011). Linear wireless sensor networks: Classification and applications. Journal of Network and Computer Applications, 34, 1671–1682.

    Article  Google Scholar 

  3. Varshney, S, Kumar, C., & Swaroop, A. (2015). Linear sensor networks: Applications, issues and major research trends. In 2015 international conference on computing, communication and automation (ICCCA). IEEE.

  4. Pan, J., Hou, Y. T., Cai, L., Shi, Y., & Shen, S. X. (2003). Topology control for wireless video surveillance networks. In Proceedings of ACM mobicom 2003. ACM.

  5. Hou, Y. T., Shi, Y., & Sherali, H. D. (2003). On energy provisioning and relaying node placement for wireless sensor networks. Technical report, Virginia Tech.

  6. Azubogu A. C., Idigo, V. E., Nnebe, S. U., & Oguejiofor, O. S. (2013). Wireless sensor networks for long distance pipeline monitoring. In World Academy of Science.

  7. Ma, M., & Yang, Y. (2007). Sencar: An energy-efficient data gathering mechanism for large-scale multihop sensor networks. IEEE Transactions on Parallel and Distributed Systems, 18(10), 1476–1488.

    Article  Google Scholar 

  8. Perillo, M., Cheng, Z., & Heinzelman, W. (2004). On the problem of unbalanced load distribution in wireless sensor networks. In IEEE globecom 2004. Dallas, TX: IEEE.

  9. Hong, L., & Xu, S. (2010). Energy-efficient node placement in linear wireless sensor networks. In 2010 international conference on measuring technology and mechatronics automation (ICMTMA) (Vol. 2, pp. 104–107). IEEE 2010 March.

  10. Gupta, S., Rana, A., & Kansal, V. (2020). Optimization in wireless sensor network using soft computing. In Proceedings of the third international conference on computational intelligence and informatics. Advances in intelligent systems and computing (Vol 1090, pp 801–810). Singapore: Springer. doi: https://doi.org/10.1007/978-981-15-1480-7_74.

  11. Pandey, P., Kansal, V., & Swaroop, A. (2020). Vehicular ad-hoc networks (VANETs): Architecture, challenges and applications. In Book titled “handling priority inversion in time-constrained distributed databases (pp. 224–239). IGI Global, https://doi.org/10.4018/978-1-7998-2491-6.ch013.0.

  12. Pandey, P. K., Swaroop, A., & Kansal, V. (2019). A concise survey on recent routing protocols for vehicular ad hoc networks (VANETs). In: 2019 international conference on computing, communication, and intelligent systems (ICCCIS), Greater Noida, India (pp. 188–193). https://doi.org/10.1109/icccis48478.2019.8974464.

  13. Rebai, M., Snoussi, H., Khoukhi, L., & Hnaien, F. (2013). Linear models for the total coverage problem in wireless sensor networks. In 2013 5th international conference on modeling, simulation and applied optimization (ICMSAO) (pp. 1–4). IEEE 2013, April.

  14. Hossain, A., Radhika, T., Chakrabarti, S., & Biswas, P. K. (2008). An approach to increase the lifetime of a linear array of wireless sensor nodes. International Journal of Wireless Information Networks, 15(2), 72–81.

    Article  Google Scholar 

  15. He, B., & Li, G. (2014). PUAR: Performance and usage aware routing algorithm for long and linear wireless sensor networks. International Journal of Distributed Sensor Networks, 10, 464963.

    Article  Google Scholar 

  16. Sun, X., He, J., Chen, Y., Ma, S., & Zhang, Z. (2011). A new routing algorithm for linear wireless sensor networks. In 2011 6th international conference on pervasive computing and applications (ICPCA) (pp. 497–501). IEEE October 2011.

  17. Jawhar, I., Mohamed, N., Mohamed, M. M., & Aziz, J. (2008). A routing protocol and addressing scheme for oil, gas, and water pipeline monitoring using wireless sensor networks. In 5th IFIP international conference on wireless and optical communications networks, 2008. WOCN’08. (pp. 1–5). IEEE May 2008.

  18. Zimmerling, M., Dargie, W., & Reason, J. M. (2007). Energy-efficient routing in linear wireless sensor networks. In IEEE international conference on mobile adhoc and sensor systems, 2007. MASS 2007 (pp. 1–3). IEEE October 2007.

  19. Skulic, J., Gkelias, A., & Leung, K. K. (2013) Node placement in linear wireless sensor networks. In 2013 Proceedings of the 21st European signal processing conference (EUSIPCO) (pp. 1–5). IEEE September 2013.

  20. Guo, Y., Kong, F., Zhu, D., Tosun, A. S., & Deng, Q. (XXXX). Sensor placement for lifetime maximization in monitoring oil pipelines.

  21. Abbas, M. Z., Bakar, K. A., Ayaz, M., & Mohamed, M. H. (2018). An overview of routing techniques for road and pipeline monitoring in linear sensor networks. Wireless Networks, 24(6), 2133–2143.

    Article  Google Scholar 

  22. Abbas, M. Z., Baker, K. A., Ayaz, M., Mohamed, H., Tariq, M., Ahmed, A., et al. (2018). Key factors involved in pipeline monitoring techniques using robots and WSNs: Comprehensive survey. Journal of Pipeline Systems Engineering and Practice, 9(2), 04018001.

    Article  Google Scholar 

  23. Abdelhafidh, M., ChaariFourati, L., Fourati, M., & Abidi, A. (2017). Hybrid mechanism for remote water pipeline monitoring system. In 2017 13th international wireless communications and mobile computing conference (IWCMC) (pp. 2140–2145). IEEE.

  24. Abdelhafidh, M., Fourati, M., ChaariFourati, L., & Laabidi, A. (2018). An investigation on wireless sensor networks pipeline monitoring system. International Journal of Wireless and Mobile Computing, 14(1), 25–46.

    Article  Google Scholar 

  25. Boussaï, D. I., Lepagnot, J., & Siarry, P. (2013). A survey on optimization metaheuristics. Information Sciences, 237, 82–117.

    Article  MathSciNet  Google Scholar 

  26. Wang, J., Cao, Y., Li, B., Kim, H.-J., & Lee, S. (2017). Particle swarm optimization based clustering algorithm with mobile sink for WSNs. Future Generation Computer Systems, 76, 452–457.

    Article  Google Scholar 

  27. Wang, J., Cao, J., Sherratt, R. S., & Park, J. H. (2018). An improved ant colony optimization-based approach with mobile sink for wireless sensor networks. The Journal of Supercomputing, 74(12), 6633–6645.

    Article  Google Scholar 

  28. Yazdani, M., & Jolai, F. (2016). Lion optimization algorithm (LOA): A nature-inspired metaheuristic algorithm. Journal of Computational Design and Engineering., 3(1), 24–36.

    Article  Google Scholar 

  29. Nematollahi, A. F., Rahiminejad, A., & Vahidi, B. (2017). A novel physical based meta-heuristic optimization method known as lightning attachment procedure optimization. Applied Soft Computing, 59, 596–621.

    Article  Google Scholar 

  30. Elnaggar, E. O., Ramadan, R. A., & Fayek, M. B. (2015). WSN in monitoring oil pipelines using ACO and GA. Procedia Computer Science, 52, 1198–1205.

    Article  Google Scholar 

  31. Varshney, S., Kumar, C., Swaroop, A., Khanna, A., Gupta, D., Rodrigues, J., et al. (2018). Energy efficient management of pipelines in buildings using linear wireless sensor networks. Sensors, 18(8), 2618.

    Article  Google Scholar 

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Indian Institute of Technology, Dhanbad, 826004, India

    Sudeep Varshney & Chiranjeev Kumar

  2. Department of Information and Technology, BPIT, New Delhi, 110094, India

    Abhishek Swaroop

Authors
  1. Sudeep Varshney
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  2. Chiranjeev Kumar
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  3. Abhishek Swaroop
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Correspondence to Sudeep Varshney.

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Varshney, S., Kumar, C. & Swaroop, A. Lightning-Based Lion Optimization Algorithm for Monitoring the Pipelines Using Linear Wireless Sensor Network. Wireless Pers Commun 117, 2475–2494 (2021). https://doi.org/10.1007/s11277-020-07987-8

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  • DOI: https://doi.org/10.1007/s11277-020-07987-8

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