Optimized heuristic LEACH variants for energy-efficient routing in passive optical networks
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Ashima
Abstract
To increase scalability and energy economy in Optical Wireless Sensor Networks (OWSNs), LEACH (Low Energy Adaptive Clustering Hierarchy) and its variants have been exhaustively investigated. Random LEACH selects cluster heads (CHs) probabilistically to maximize energy consumption; LEACH-C builds on this by selecting CHs dependent on residual energy, so greatly extending network lifetime. By means of further combination of dynamic clustering and load balancing, the proposed modified LEACH-C algorithm guarantees constant cluster sizes and efficient energy distribution. Based on simulation results, strong solutions for OWSNs: modified LEACH-C beats random LEACH-C in obtaining longer network lifetime (1,353 rounds) and higher communication efficiency. Computational complexity, communication overhead, load balancing difficulties, and scalability constraints are the challenges that need to be addressed. Node configurations and large-scale projects drawing attention to these challenges. If performance we want to increase performance and address these challenges, future directions demand the integration of hybrid energy models, adaptive reclustering systems, and machine learning for dynamic CH selection. Moreover quite essential for guaranteeing the resilience and adaptability of Modified LEACH-C in various WSN environments are security enhancements and practical testing.
Acknowledgments
Thanks to all my coauthors for the support.
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Research ethics: Na.
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Informed consent: We all are fully responsible for this paper.
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Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.
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Use of Large Language Models, AI and Machine Learning Tools: None declared.
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Conflict of interest: The authors state no conflict of interest.
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Research funding: None declared.
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Data availability: Not applicable.
References
1. Huang, Y, Wen, M, Lee, C, Chae, CB, Ji, F. A two-way molecular communication assisted by an impulsive force. IEEE Trans Ind Inf 2019;15:3048–57. https://doi.org/10.1109/tii.2019.2897066.Search in Google Scholar
2. Singh, J, Kaur, R, Singh, D. A survey and taxonomy on energy management schemes in wireless sensor networks. J Syst Architect 2020;111:101782. https://doi.org/10.1016/j.sysarc.2020.101782.Search in Google Scholar
3. Wu, Y, Li, B, Zhu, Y, Liu, W. Energy-neutral communication protocol for living-tree bioenergy-powered wireless sensor network. Mob Inf Syst 2018;2018. https://doi.org/10.1155/2018/5294026.Search in Google Scholar
4. Rajesh, BM, Thanamani, AS, Chithra, B, FinnyBelwin, A, LindaSherin, A. Adaptive weight butterfly optimization algorithm (AWBOA) based cluster head selection (CHS) and optimized energy efficient cluster based scheduling (OEECS) approach in wireless sensor networks (WSNS). Int J Syst Assur Eng Manag 2022:1–14. https://doi.org/10.1007/s13198-022-01726-x.Search in Google Scholar
5. Alabady, SA, Salleh, MFM. Binary joint network-channel coding for reliable multi-hop wireless networks. ECTI Trans Electr Eng, Electron Commun 2021;19:23–33. https://doi.org/10.37936/ecti-eec.2021191.222590.Search in Google Scholar
6. Vimal, V, Singh, KU, Kumar, A, Gupta, SK, Rashid, M, Saket, RK, et al.. Clustering isolated nodes to enhance network’s life time of WSNs for IoT applications. IEEE Syst J 2021;15:5654–63. https://doi.org/10.1109/jsyst.2021.3103696.Search in Google Scholar
7. Abasikeles-Turgut, I. DiCDU: distributed clustering with decreased uncovered nodes for WSNs. IET Commun 2020;14:974–81. https://doi.org/10.1049/iet-com.2019.0629.Search in Google Scholar
8. Anil, GL, Iqbal, JM. Implementation of energy efficient circuit design using a* algorithm in embedded network. Microprocess Microsyst 2020;74:103034. https://doi.org/10.1016/j.micpro.2020.103034.Search in Google Scholar
9. Al-Khammasi, S, Alhelal, D, Ali, NS. Energy efficient cluster based routing protocol for dynamic and static nodes in wireless sensor network. TELKOMNIKA (Telecommun Comput Electron Control) 2018;16:1974–81. https://doi.org/10.12928/telkomnika.v16i5.9930.Search in Google Scholar
10. Jain, N, Bohara, VA, Gupta, A. iDEG: integrated data and energy gathering framework for practical wireless sensor networks using compressive sensing. IEEE Sens J 2018;19:1040–51. https://doi.org/10.1109/jsen.2018.2878788.Search in Google Scholar
11. Nguyen, TT, Phan, LA, Kim, T, Kim, T, Lee, J, Ham, J. Distributed TDMA scheduling using topological ordering in wireless sensor networks. In: 2019 28th International Conference on Computer Communication and Networks (ICCCN). IEEE; 2019:1–2 pp.10.1109/ICCCN.2019.8847070Search in Google Scholar
12. Batta, MS, Harous, S, Louail, L, Aliouat, Z. A distributed tdma scheduling algorithm for latency minimization in internet of things. In: 2019 IEEE International Conference on Electro Information Technology (EIT). IEEE; 2019:108–13 pp.10.1109/EIT.2019.8833679Search in Google Scholar
13. Zhang, X, Tao, L, Yan, F, Sung, DK. Shortest-latency opportunistic routing in asynchronous wireless sensor networks with independent dutycycling. IEEE Trans Mobile Comput 2019;19:711–23. https://doi.org/10.1109/tmc.2019.2897998.Search in Google Scholar
14. Chauhan, V, Soni, S. Variable duty cycle aware energy efficient clustering strategy for wireless sensor networks. J Ambient Intell Hum Comput 2022:1–13. https://doi.org/10.1007/s12652-022-04363-1.Search in Google Scholar
15. Sadowski, S, Spachos, P. Wireless technologies for smart agricultural monitoring using internet of things devices with energy harvesting capabilities. Comput Electron Agric 2020;172:105338. https://doi.org/10.1016/j.compag.2020.105338.Search in Google Scholar
16. Mohammadi, R, Nazari, A, Nassiri, M, Conti, M. An SDN-based framework for QoS routing in internet of underwater things. Telecommun Syst 2021;78:253–66. https://doi.org/10.1007/s11235-021-00812-y.Search in Google Scholar
17. Math, RKM, Dharwadkar, NV. IoT based low-cost weather station and monitoring system for precision agriculture in India. In: 2018 2nd international conference on I-SMAC (IoT in social, mobile, analytics and cloud)(ISMAC) I-SMAC (IoT in social, mobile, analytics and cloud)(I-SMAC), 2018 2nd international conference on. IEEE; 2018:81–6 pp.10.1109/I-SMAC.2018.8653749Search in Google Scholar
18. Radhika, M, Sivakumar, P. Energy optimized micro genetic algorithm based LEACH protocol for WSN. Wirel Netw 2021;27:27–40. https://doi.org/10.1007/s11276-020-02435-8.Search in Google Scholar
19. Kishorebabu, V, Sravanthi, R. Real time monitoring of environmental parameters using IOT. Wirel Pers Commun 2020;112:785–808. https://doi.org/10.1007/s11277-020-07074-y.Search in Google Scholar
20. Sharma, D, Ojha, A, Bhondekar, AP. Heterogeneity consideration in wireless sensor networks routing algorithms: a review. J Supercomput 2019;75:2341–2394. https://doi.org/10.1007/s11227-018-2635-8.Search in Google Scholar
21. Abidi, B, Jilbab, A, El Haziti, M. Routing protocols for wireless sensor networks: a survey. In: Advances in Ubiquitous Computing. Academic Press; 2020:3–15 pp.10.1016/B978-0-12-816801-1.00001-3Search in Google Scholar
22. Kumar, MP, Hariharan, R. SPEED-UP, and energy-efficient GPSR protocol for WSNs using IOT. Meas: Sens 2022:100411. https://doi.org/10.1016/j.measen.2022.100411.Search in Google Scholar
23. Bharany, S, Sharma, S, Badotra, S, Khalaf, OI, Alotaibi, Y, Alghamdi, S, et al.. Energy-efficient clustering scheme for flying ad-hoc networks using an optimized LEACH protocol. Energies 2021;14:6016. https://doi.org/10.3390/en14196016.Search in Google Scholar
24. Torrisi. Autonomous energy status sharing and synchronization for batteryless sensor networks. In: Proceedings of the 19th ACM Conference on Embedded Networked Sensor Systems; 2021:569–71 pp.10.1145/3485730.3493360Search in Google Scholar
25. Trüb, R, Da Forno, R, Daschinger, L, Biri, A, Beutel, J, Thiele, L. Non-intrusive distributed tracing of wireless IoT devices with the FlockLab 2 testbed. ACM Trans Internet of Things 2021;3:1–31. https://doi.org/10.1145/3480248.Search in Google Scholar
26. Fanucchi, D, Righetti, F, Vallati, C, Staehle, B, Anastasi, G. Improving link quality estimation accuracy in 6tisch networks. In: 2019 Sixth International Conference on Internet of Things: Systems, Management and Security (IOTSMS). IEEE; 2019:243–50 pp.10.1109/IOTSMS48152.2019.8939167Search in Google Scholar
27. Zorbas, D, Caillouet, C, Abdelfadeel Hassan, K, Pesch, D. Optimal data collection time in LoRa networks–A time-slotted approach. Sensors 2021;21:1193. https://doi.org/10.3390/s21041193.Search in Google Scholar PubMed PubMed Central
28. Ramasamy, LK, KP, FK, Imoize, AL, Ogbebor, JO, Kadry, S, Rho, S. Blockchain-based wireless sensor networks for malicious node detection: a survey. IEEE Access 2021;9:128765–85. https://doi.org/10.1109/access.2021.3111923.Search in Google Scholar
29. Khashan, OA, Ahmad, R, Khafajah, NM. An automated lightweight encryption scheme for secure and energy-efficient communication in wireless sensor networks. Ad Hoc Netw 2021;115:102448. https://doi.org/10.1016/j.adhoc.2021.102448.Search in Google Scholar
30. Sivaram, M, Rohini, R, Rajanarayanan, S, Maseleno, A, Mohammed, AS, Fareed Ibrahim, B, et al.. Efficient coverage greedy packet stateless routing in wireless sensor networks. Meas Control 2020;53:1116–21. https://doi.org/10.1177/0020294020932359.Search in Google Scholar
31. Vandervelden, T, De Smet, R, Steenhaut, K, Braeken, A. SymmetricKey-Based authentication among the nodes in a wireless sensor and actuator network. Sensors 2022;22:1403. https://doi.org/10.3390/s22041403.Search in Google Scholar PubMed PubMed Central
32. Alshrif, FF, Sundararajan, EA, Ahmad, R, Alkhatib, Y. New framework for authentication and key establishment to secure 6LoWPAN networks. In: 2021 International Conference on Electrical Engineering and Informatics (ICEEI). IEEE; 2021:1–6 pp.10.1109/ICEEI52609.2021.9611135Search in Google Scholar
33. Sharma, S, Bansal, RK, Bansal, S. Issues and challenges in wireless sensor networks. In: 2013 international conference on machine intelligence and research advancement. IEEE; 2013:58–62 pp.10.1109/ICMIRA.2013.18Search in Google Scholar
34. Balen, J, Zagar, D, Martinovic, G. Quality of service in wireless sensor networks: a survey and related patents. Recent Pat Comput Sci 2011;4:188–202. https://doi.org/10.2174/2213275911104030188.Search in Google Scholar
35. Pundir, M, Sandhu, JK, Kumar, A. Quality-of-service prediction techniques for wireless sensor networks. J Phys Conf 2021;1950:012082. https://doi.org/10.1088/1742-6596/1950/1/012082.Search in Google Scholar
36. Khan, MK, Shiraz, M, Shaheen, Q, Butt, SA, Akhtar, R, Khan, MA, et al.. Hierarchical routing protocols for wireless sensor networks: functional and performance analysis. J Sens 2021;2021. https://doi.org/10.1155/2021/7459368.Search in Google Scholar
37. Ebrahimi, N, Taghavirashidizadeh, A, Hosseini, SS. Extend the lifetime of wireless sensor networks by modifying cluster-based data collection. arXiv preprint arXiv:2207.08018. 2022.Search in Google Scholar
38. Mukti, FS, Lorenzo, JE, Zuhdianto, R, Junikhah, A, Soetedjo, A, Krismanto, AU. A comprehensive performance evaluation of proactive, reactive and hybrid routing in wireless sensor network for real time monitoring system. In: 2021 International Conference on Computer Science and Engineering (IC2SE). IEEE; 2021, vol 1:1–6 pp.10.1109/IC2SE52832.2021.9791992Search in Google Scholar
39. Gupta, SK, Singh, S. Survey on energy efficient dynamic sink optimum routing for wireless sensor network and communication technologies. Int J Commun Syst 2022;e5194. https://doi.org/10.1002/dac.5194.Search in Google Scholar
40. Majid, M, Habib, S, Javed, AR, Rizwan, M, Srivastava, G, Gadekallu, TR, et al.. Applications of wireless sensor networks and internet of things frameworks in the industry revolution 4.0: a systematic literature review. Sensors 2022;22:2087. https://doi.org/10.3390/s22062087.Search in Google Scholar PubMed PubMed Central
41. Amutha, J, Sharma, S, Sharma, SK. Strategies based on various aspects of clustering in wireless sensor networks using classical, optimization and machine learning techniques: review, taxonomy, research findings, challenges and future directions. Comput Sci Rev 2021;40:100376. https://doi.org/10.1016/j.cosrev.2021.100376.Search in Google Scholar
42. Osamy, W, Khedr, AM, Salim, A, AlAli, AI, El-Sawy, AA. Recent studies utilizing artificial intelligence techniques for solving data collection, aggregation and dissemination challenges in wireless sensor networks: a review. Electronics 2022;11:313. https://doi.org/10.3390/electronics11030313.Search in Google Scholar
43. Pundir, M, Sandhu, JK. A systematic review of quality of service in wireless sensor networks using machine learning: recent trend and future vision. J Netw Comput Appl 2021;188:103084. https://doi.org/10.1016/j.jnca.2021.103084.Search in Google Scholar
44. Jagan, GC, JesuJayarin, P. Wireless sensor network cluster head selection and short routing using energy efficient ElectroStatic discharge algorithm. J Eng 2022;2022. https://doi.org/10.1155/2022/8429285.Search in Google Scholar
45. Daanoune, I, Abdennaceur, B, Ballouk, A. A comprehensive survey on LEACH-based clustering routing protocols in wireless sensor networks. Ad Hoc Netw 2021;114:102409. https://doi.org/10.1016/j.adhoc.2020.102409.Search in Google Scholar
46. Chaurasia, S, Kumar, K, Kumar, N. EEM-CRP: Energy efficient meta-heuristic cluster based routing protocol for WSNs. IEEE Sens J 2023. [Online]. Available: Link. https://doi.org/10.1109/jsen.2023.3322631.Search in Google Scholar
47. Priyadarshi, R. Energy-efficient routing in wireless sensor networks: a meta-heuristic and artificial intelligence-based approach. Arch Comput Methods Eng 2024. [Online]. Available: Link.10.1007/s11831-023-10039-6Search in Google Scholar
48. Abose, TA, Kejela, DC. Improving wireless sensor network lifespan with optimized clustering probabilities. Heliyon 2024. [Online]. Available: Link.Search in Google Scholar
49. Daanoune, I, Abdennaceur, B, Ballouk, A. A comprehensive survey on LEACH-based clustering routing protocols in WSN. Ad Hoc Netw 2024. [Online]. Available: Link. https://doi.org/10.1016/j.adhoc.2020.102409.Search in Google Scholar
50. Sambhe, N, Yenurkar, G. A comparative analysis using LEACH protocol to enhance energy efficiency in wireless sensor networks. Springer; 2024. [Online]. Available: Link.10.1007/s10791-024-09495-wSearch in Google Scholar
51. Kuppusamy, L. A hybrid approach to energy efficient clustering and routing in wireless sensor networks. Evol Intell 2024. [Online]. Available: Link.Search in Google Scholar
52. Saha, R, Biswas, S. Sink mobility-based energy efficient routing algorithm variants in WSN. Springer; 2024. [Online]. Available: Link.Search in Google Scholar
53. Zhang, H, Liu, C. A reviewon node deployment of wireless sensor network. IJCSI Int J Comput Sci Issues 2012;9:378–83.Search in Google Scholar
54. Jain, K, Mehra, PS, Dwivedi, AK, Agarwal, A. SCADA: scalable cluster-based data aggregation technique for improving network lifetime of wireless sensor networks. J Supercomput 2022:1–29. https://doi.org/10.1007/s11227-022-04419-1.Search in Google Scholar
55. Heinzelman, WB, Chandrakasan, AP, Balakrishnan, H. Anapplication-specific protocol architecture for wirelessmicro sensor networks. IEEE Trans Wireless Commun 2002;1:660–70. https://doi.org/10.1109/twc.2002.804190.Search in Google Scholar
56. Lindsey, S, Raghavendra, CS. “PEGASIS:Power efficient GAtheringin sensor information systems”. In: The Proceedings of the IEEE Aerospace Conference. BigSky, Montana; 2002.Search in Google Scholar
57. Iram, R, SheikhM, I, Jabbar, S, Minhas, AA. Computational intelligence based optimization of energy aware routingin WSN. In: Proceedings of the World Congresson Engineering and Computer Science. SanFrancisco, USA, vol I; 2011. October19-21,2.Search in Google Scholar
58. Jiang, H, Sun, Y, Sun, R, Xu, H. “Fuzzy-logic based energy optimized routing for wireless sensor networks”. Int J Distr Sens Netw Vol 2013:8.10.1155/2013/216561Search in Google Scholar
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