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Energy Efficient Routing in Wireless Sensor Network for Moving Nodes Using Genetic Algorithm Compared with PSO

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Advanced Communication and Intelligent Systems (ICACIS 2022)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1749))

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Abstract

The objective of the research work is to examine energy-efficient routing in wireless sensor networks for moving nodes by contrasting new evolutionary algorithms with the Particle Swarm Optimization (PSO) Algorithm. Comparative analysis of energy efficient routing is performed by a novel genetic algorithm where there are several samples (N = 10) and a PSO algorithm where there are several samples (N = 10) techniques with pre-test power of 80% using NS2. When routing wireless sensor networks with moving nodes, Various metrics, including delay, energy use, and packet delivery ratio, are used to compare PSO and genetic algorithms. The evolutionary algorithm outperforms the PSO algorithm in these ways in terms of packet delivery ratio, energy usage, and delay. (p < 0.05) indicates a statistically significant difference. The research's findings comprised the three metrics of delay, energy consumption and packet delivery ratio. The method shows that the novel Genetic algorithm outperforms the PSO algorithm for wireless sensor network energy-efficient routing for moving nodes by identifying a set of routes that can satisfy the delay restrictions.

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References

  1. Femila, L., Marsaline Beno, M.: Optimizing transmission power and energy efficient routing protocol in MANETs. Wireless Pers. Commun. 106(3), 1041–1056 (2019). https://doi.org/10.1007/s11277-019-06202-7

    Article  Google Scholar 

  2. Saritha, V., Venkata Krishna, P., Alagiri, I., Madhu Viswanatham, V., Obaidat, M.S.: Efficient multipath routing protocol with quality of service for mobile ad hoc networks. In: 2018 IEEE International Conference on Communications (ICC) (2018). https://doi.org/10.1109/icc.2018.8422385

  3. Gogu, A., Nace, D., Dilo, A., Meratni, N.: Review of optimization problems in wireless sensor networks. Telecommun. Netw. Curr. Status Future Trends (2012). https://doi.org/10.5772/38360

    Article  Google Scholar 

  4. Yick, J., Mukherjee, B., Ghosal, D.: Wireless sensor network survey. Comput. Netw. 52(12), 2292–2330 (2008). https://doi.org/10.1016/j.comnet.2008.04.002

    Article  Google Scholar 

  5. Fu, X., Fortino, G., Li, W.: Environment-cognitive multipath routing protocol in wireless sensor networks. In: 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC) (2018). https://doi.org/10.1109/smc.2018.00471

  6. Aashkaar, M., Sharma, P.: Enhanced energy efficient AODV routing protocol for MANET. In: 2016 International Conference on Research Advances in Integrated Navigation Systems (RAINS) (2016). https://doi.org/10.1109/rains.2016.7764376

  7. Choudhary, R., Sharma, P.K.: An efficient approach for power aware routing protocol for MANETs using genetic algorithm. In: Rathore, V.S., Worring, M., Mishra, D.K., Joshi, A., Maheshwari, S. (eds.) Emerging Trends in Expert Applications and Security. AISC, vol. 841, pp. 133–138. Springer, Singapore (2019). https://doi.org/10.1007/978-981-13-2285-3_17

    Chapter  Google Scholar 

  8. Pandey, K.K., Saud, B., Kumari, B., Biswas, S.: An energy efficient hierarchical clustering technique for wireless sensor network. In: 2016 Fourth International Conference on Parallel, Distributed and Grid Computing (PDGC) (2016). https://doi.org/10.1109/pdgc.2016.7913184

  9. Banerjee, A., et al.: Construction of effective wireless sensor network for smart communication using modified ant colony optimization technique. In: Bianchini, M., Piuri, V., Das, S., Shaw, R.N. (eds.) Advanced Computing and Intelligent Technologies. LNNS, vol. 218, pp. 269–278. Springer, Singapore (2022). https://doi.org/10.1007/978-981-16-2164-2_22

    Chapter  Google Scholar 

  10. Li, Z., Lei, L.: Sensor node deployment in wireless sensor networks based on improved particle swarm optimization. In: 2009 International Conference on Applied Superconductivity and Electromagnetic Devices (2009). https://doi.org/10.1109/asemd.2009.5306655

  11. Feng, W., et al.: Joint energy-saving scheduling and secure routing for critical event reporting in wireless sensor networks. IEEE Access 8, 53281–53292 (2020). https://doi.org/10.1109/access.2020.2981115

    Article  Google Scholar 

  12. Paul, A., Sinha, S., Shaw, R.N., Ghosh, A.: A neuro-fuzzy based IDS for internet-integrated WSN. In: Bansal, J.C., Paprzycki, M., Bianchini, M., Das, S. (eds.) Computationally Intelligent Systems and their Applications. SCI, vol. 950, pp. 71–86. Springer, Singapore (2021). https://doi.org/10.1007/978-981-16-0407-2_6

    Chapter  Google Scholar 

  13. Badni, A.B., and Smt Kamala Sri Venkappa M Agadi college of Engineering and Technology: Energy efficiency routing of wireless sensor networks utilizing particle swarm optimization and LEACH protocol Int. J. Eng. Res. Technol. (Ahmedabad) V9(06) (2020). https://doi.org/10.17577/ijertv9is060219

  14. Burgos, U., Amozarrain, U., Gómez-Calzado, C., Lafuente, A.: Routing in mobile wireless sensor networks: a leader-based approach. Sensors 17(7), 1587 (2017). https://doi.org/10.3390/s17071587

    Article  Google Scholar 

  15. Zungeru, A.M., Seng, K.P., Ang, L.-M., Chia, W.C.: Energy efficiency performance improvements for ant-based routing algorithm in wireless sensor networks. J. Sens. 2013, 1–17 (2013). https://doi.org/10.1155/2013/759654

    Article  Google Scholar 

  16. Nandan, A.S., Singh, S., Awasthi, L.K.: An efficient cluster head election based on optimized genetic algorithm for movable sinks in IoT enabled HWSNs. Appl. Soft Comput. 107. 107318 (2021). https://doi.org/10.1016/j.asoc.2021.107318

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Kumar, R.L.P., Vijayalakshmi (2023). Energy Efficient Routing in Wireless Sensor Network for Moving Nodes Using Genetic Algorithm Compared with PSO. In: Shaw, R.N., Paprzycki, M., Ghosh, A. (eds) Advanced Communication and Intelligent Systems. ICACIS 2022. Communications in Computer and Information Science, vol 1749. Springer, Cham. https://doi.org/10.1007/978-3-031-25088-0_54

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  • DOI: https://doi.org/10.1007/978-3-031-25088-0_54

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