Hierarchical path algorithm for data collection in order to reduce energy consumption in wireless sensor networks with mobile sink
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Hasan Sadeghzadeh , Reza Etebari *1  |
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Abstract: (350 Views) |
Abstract:
Recently, wireless sensor networks have attracted wide attention. In these networks, each sensor node has limited energy, which cannot be recharged after being deployed in the environment. As a result, one of the most important challenges of this type of network is managing the energy consumption of the nodes, which aims to increase the lifetime of the entire network. Therefore, in this article, in order to reduce energy consumption, we first cluster the nodes based on the three criteria of the amount of energy of each node, the centrality of each node, and the density of nodes. After clustering, in each cluster, the node with the highest amount of energy is selected as the head of the cluster. fter the member nodes give the data to the cluster heads, the cluster heads send the data to the nearest cluster head. Finally, the information of all nodes reaches the sink. At the end, a comparison was made between the proposed method and LEACH, and the results show that the proposed method has reduced the energy consumption by 38% compared to the LEACH method. |
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Keywords: ey words: Wireless sensor networks, routing, energy consumption management, mobile sink |
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Type of Study: Research |
Received: 2024/01/30 | Accepted: 2025/01/5 | Published: 2025/04/6
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References |
1. [1]Wang, J., Gao, Y., Liu, W., Sangaiah, A. K., & Kim, H. J. (2019). Energy efficient routing algorithm with mobile sink support for wireless sensor networks. Sensors, 19(7), 1494 [ DOI:10.3390/s19071494] 2. [2]Jha, S. K., & Eyong, E. M. (2018). An energy optimization in wireless sensor networks by using genetic algorithm. Telecommunication Systems, 67(1), 113-121 [ DOI:10.1007/s11235-017-0324-1] 3. [3]Vijayashree, R., & Suresh Ghana Dhas, C. (2019). Energy efficient data collection with multiple mobile sink using artificial [ DOI:10.1080/00051144.2019.1666548] 4. bee colony algorithm in large-scale WSN. Automatika: časopis za automatiku, mjerenje, elektroniku, računarstvo i komunikacije, 60(5), 555-563 5. [4]Bhola, J., Soni, S., & Cheema, G. K. (2020). Genetic algorithm based optimized leach protocol for energy efficient wireless sensor networks. Journal of Ambient Intelligence and Humanized Computing, 11(3), 1281-1288 [ DOI:10.1007/s12652-019-01382-3] 6. [5]Kumar, N., & Kaur, J. (2011, September). Improved leach protocol for wireless sensor networks. In 2011 7th International [ DOI:10.1109/wicom.2011.6040360] 7. Conference on Wireless Communications, Networking and Mobile Computing (pp. 1-5). IEEE. 8. [6]Bayraklı, S., & Erdogan, S. Z. (2012). Genetic algorithm based energy efficient clusters (GABEEC) in wireless sensor networks. Procedia Computer Science, 10, 247-254. [ DOI:10.1016/j.procs.2012.06.034] 9. [7]Rawat, P., Singh, K. D., Chaouchi, H., & Bonnin, J. M. (2014). Wireless sensor networks: a survey on recent developments and potential synergies. The Journal of supercomputing, 68, 1-48. [ DOI:10.1007/s11227-013-1021-9] 10. [8]Yue, Y., Li, J., Fan, H., & Qin, Q. (2016). Optimization-based artificial bee colony algorithm for data collection in large-scale mobile wireless sensor networks. Journal of Sensors, 2016 [ DOI:10.1155/2016/7057490] 11. [9]Pantazis, N. A., Nikolidakis, S. A., & Vergados, D. D. (2012). Energy-efficient routing protocols in wireless sensor networks: A survey. IEEE Communications surveys & tutorials, 15(2), 551-591. [ DOI:10.1109/SURV.2012.062612.00084] 12. [10]Reddy, D. L., Puttamadappa, C., & Suresh, H. N. (2021). Merged glowworm swarm with ant colony optimization for energy efficient clustering and routing in wireless sensor network. Pervasive and Mobile Computing, 71, 101338 [ DOI:10.1016/j.pmcj.2021.101338] 13. [11]Singh, M. K., Amin, S. I., & Choudhary, A. (2021). Genetic algorithm based sink mobility for energy efficient data routing in wireless sensor networks. AEU-International Journal of Electronics and Communications, 131, 153605 [ DOI:10.1016/j.aeue.2021.153605] 14. [12]Wang, J., Gao, Y., Zhou, C., Sherratt, S., & Wang, L. (2020). Optimal coverage multi-path scheduling scheme with multiple mobile sinks for WSNs. Computers, Materials & Continua, 62(2), 695-711. [ DOI:10.32604/cmc.2020.08674] 15. [13]Asadi, B. (2021). Routing optimization in Wireless Sensor Networks to increase network life by managing network energy. Journal of Computational Statistics and Modeling, 1(2), 147-163. 16. [14]Mahboub, A., & Arioua, M. (2017). Energy-efficient hybrid 17. k-means algorithm for clustered wireless sensor networks. International Journal of Electrical and Computer Engineering, 7(4), 2054
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sadeghzadeh H, etebari R. Hierarchical path algorithm for data collection in order to reduce energy consumption in wireless sensor networks with mobile sink. ieijqp 2024; 13 (3) URL: http://ieijqp.ir/article-1-984-en.html
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