{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,23]],"date-time":"2026-08-23T17:33:19Z","timestamp":1787506399070,"version":"build-2736575974"},"reference-count":28,"publisher":"MDPI AG","issue":"13","license":[{"start":{"date-parts":[[2024,7,7]],"date-time":"2024-07-07T00:00:00Z","timestamp":1720310400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Korea government(MSIT)","award":["RS-2023-00229801"],"award-info":[{"award-number":["RS-2023-00229801"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>As an alternative to flat architectures, clustering architectures are designed to minimize the total energy consumption of sensor networks. Nonetheless, sensor nodes experience increased energy consumption during data transmission, leading to a rapid depletion of energy levels as data are routed towards the base station. Although numerous strategies have been developed to address these challenges and enhance the energy efficiency of networks, the formulation of a clustering-based routing algorithm that achieves both high energy efficiency and increased packet transmission rate for large-scale sensor networks remains an NP-hard problem. Accordingly, the proposed work formulated an energy-efficient clustering mechanism using a chaotic genetic algorithm, and subsequently developed an energy-saving routing system using a bio-inspired grey wolf optimizer algorithm. The proposed chaotic genetic algorithm\u2013grey wolf optimization (CGA-GWO) method is designed to minimize overall energy consumption by selecting energy-aware cluster heads and creating an optimal routing path to reach the base station. The simulation results demonstrate the enhanced functionality of the proposed system when associated with three more relevant systems, considering metrics such as the number of live nodes, average remaining energy level, packet delivery ratio, and overhead associated with cluster formation and routing.<\/jats:p>","DOI":"10.3390\/s24134406","type":"journal-article","created":{"date-parts":[[2024,7,8]],"date-time":"2024-07-08T09:01:19Z","timestamp":1720429279000},"page":"4406","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["Clustered Routing Using Chaotic Genetic Algorithm with Grey Wolf Optimization to Enhance Energy Efficiency in Sensor Networks"],"prefix":"10.3390","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5206-635X","authenticated-orcid":false,"given":"Halimjon","family":"Khujamatov","sequence":"first","affiliation":[{"name":"Department of Computer Engineering, Gachon University, Seognam-daero, Sujeong-gu, Seongnam-si 1342, Gyeonggi-do, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4058-7718","authenticated-orcid":false,"given":"Mohaideen","family":"Pitchai","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, National Engineering College, Kovilpatti 627011, Tamilnadu, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alibek","family":"Shamsiev","sequence":"additional","affiliation":[{"name":"Department of Data Communication Networks and Systems, Tashkent University of Information Technologies Named after Muhammad al-Khwarizmi, Tashkent 100200, Uzbekistan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1438-0628","authenticated-orcid":false,"given":"Abdinabi","family":"Mukhamadiyev","sequence":"additional","affiliation":[{"name":"Department of Computer Engineering, Gachon University, Seognam-daero, Sujeong-gu, Seongnam-si 1342, Gyeonggi-do, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jinsoo","family":"Cho","sequence":"additional","affiliation":[{"name":"Department of Computer Engineering, Gachon University, Seognam-daero, Sujeong-gu, Seongnam-si 1342, Gyeonggi-do, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,7,7]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"e01591","DOI":"10.1016\/j.heliyon.2019.e01591","article-title":"Communication protocols for wireless sensor networks: A survey and comparison","volume":"5","author":"Ketshabetswe","year":"2019","journal-title":"Heliyon"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"4705","DOI":"10.1109\/JSEN.2019.2900094","article-title":"EUDFC\u2014Enhanced unequal distributed Type-2 fuzzy clustering algorithm","volume":"19","year":"2019","journal-title":"IEEE Sens."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Gheisari, M., Abbasi, A.A., Sayari, Z., Rizvi, Q., Asheralieva, A., Banu, S., Awaysheh, F.M., Shah, S.B.H., and Raza, K.A. (2020, January 17\u201319). A survey on clustering algorithms in wireless sensor networks: Challenges, research, and trends. Proceedings of the 2020 International Computer Symposium (ICS), Tainan, Taiwan.","DOI":"10.1109\/ICS51289.2020.00065"},{"key":"ref_4","first-page":"783","article-title":"Critical analysis of clustering algorithms for wireless sensor networks","volume":"Volume 436","author":"Bhanot","year":"2016","journal-title":"Proceedings of Fifth International Conference on Soft Computing for Problem Solving, Proceedings of the SocProS 2015, Roorkee, India, 18\u201320 December 2015"},{"key":"ref_5","first-page":"145","article-title":"Hybrid meta-heuristic optimization based energy efficient protocol for wireless sensor networks","volume":"19","author":"Kaur","year":"2018","journal-title":"Egypt. Inf. J."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1550147717741103","DOI":"10.1177\/1550147717741103","article-title":"IHSCR: Energy-efficient clustering and routing for wireless sensor networks based on harmony search algorithm","volume":"13","author":"Zeng","year":"2017","journal-title":"Int. J. Distrib. Sens. Netw."},{"key":"ref_7","unstructured":"Yang, X.S. (2010). Nature-Inspired Metaheuristic Algorithms, Luniver Press. [2nd ed.]."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"193","DOI":"10.1007\/978-3-030-66007-9_7","article-title":"Metaheuristic algorithms for wireless sensor networks","volume":"Volume 948","author":"Cuevas","year":"2021","journal-title":"Recent Metaheuristic Computation Schemes in Engineering"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Yang, X.S., and Karamanoglu, M. (2013). 1-Swarm intelligence and bio-inspired computation: An overview. Swarm Intelligence and Bio-Inspired Computation, Elsevier.","DOI":"10.1016\/B978-0-12-405163-8.00001-6"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"175","DOI":"10.1007\/s10776-021-00508-9","article-title":"A Comprehensive review on swarm intelligence-based routing protocols in wireless multimedia sensor networks","volume":"28","author":"Benmansour","year":"2021","journal-title":"Int. J. Wirel. Inf. Netw."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Ajmi, N., Helali, A., Lorenz, P., and Mghaieth, R. (2021). \u2018MWCSGA-Multi Weight Chicken Swarm Based Genetic Algorithm for Energy Efficient Clustered Wireless Sensor Network. Sensors, 21.","DOI":"10.3390\/s21030791"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"5051863","DOI":"10.1155\/2021\/5051863","article-title":"Adaptive chaotic ant colony optimization for energy optimization in smart sensor networks","volume":"2021","author":"Jia","year":"2021","journal-title":"J. Sens."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"2167","DOI":"10.1007\/s11277-022-09651-9","article-title":"Energy efficient cluster based routing protocol for WSN using firefly algorithm and ant colony optimization","volume":"125","author":"Wang","year":"2022","journal-title":"Wirel. Pers. Commun."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Majeed, D.M., Rabee, H.W., and Ma, Z. (2020, January 28\u201331). Improving energy consumption using fuzzy-GA clustering and ACO routing in WSN. Proceedings of the 2020 3rd International Conference on Artificial Intelligence and Big Data (ICAIBD), Chengdu, China.","DOI":"10.1109\/ICAIBD49809.2020.9137446"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Ram, S., Nageswara Rao, K., Basha, S.J., and Reddy, S. (2020, January 5\u20137). Cluster head and optimal path selection using K-GA and T-FA algorithms for wireless sensor networks. Proceedings of the 2020 4th International Conference on Electronics, Communication and Aerospace Technology (ICECA), Coimbatore, India.","DOI":"10.1109\/ICECA49313.2020.9297535"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"e4344","DOI":"10.1002\/dac.4344","article-title":"GWO-C: Grey wolf optimizer-based clustering scheme for WSNs","volume":"33","author":"Agrawal","year":"2020","journal-title":"Int. J. Commun."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Joseph, L.M.I.L., Deepika, G.J., Dinesh, P.S., Vijayashaarathi, S., and Samanvita, N. (2023, January 20\u201321). Modified chaotic grey wolf optimization algorithm for energy aware in WSN. Proceedings of the 2023 International Conference on Evolutionary Algorithms and Soft Computing Techniques (EASCT), Bengaluru, India.","DOI":"10.1109\/EASCT59475.2023.10393245"},{"key":"ref_18","first-page":"499","article-title":"Genetic algorithm-based energy-efficient clustering with adaptive grey wolf optimization-based multipath routing in wireless sensor network to increase network life time","volume":"Volume 431","author":"Patra","year":"2022","journal-title":"Intelligent Systems, Proceedings of the ICMIB 2021, Sarang, India, 18\u201320 December 2021"},{"key":"ref_19","first-page":"9846601","article-title":"Energy-efficient clustering and routing algorithm using hybrid fuzzy with grey wolf optimization in wireless sensor networks","volume":"2022","author":"Zaheeruddin","year":"2022","journal-title":"Sec. Commun. Netw."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"537","DOI":"10.1007\/s11277-022-09966-7","article-title":"GA-UCR: Genetic algorithm based unequal clustering and routing protocol for wireless sensor networks","volume":"128","author":"Gunjan","year":"2023","journal-title":"Wirel. Pers. Commun."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"79","DOI":"10.7763\/IJMLC.2011.V1.12","article-title":"LEACH-GA: Genetic algorithm-based energy-efficient adaptive clustering protocol for wireless sensor networks","volume":"1","author":"Liu","year":"2011","journal-title":"Int. J. Mach. Learn. Comput."},{"key":"ref_22","first-page":"163","article-title":"Chaos genetic algorithm instead genetic algorithm","volume":"12","author":"Javidi","year":"2015","journal-title":"Int. Arab. J. Inf. Technol."},{"key":"ref_23","first-page":"799","article-title":"A Chaotic Genetic Algorithm for Wireless Sensor Networks","volume":"Volume 79","author":"Yadav","year":"2018","journal-title":"Proceedings of First International Conference on Smart System, Innovations and Computing, Proceedings of the SSIC 2017, Jaipur, India, 14\u201316 April 2017"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"158082","DOI":"10.1109\/ACCESS.2020.3020158","article-title":"Energy-efficient and load-balanced clustering routing protocol for wireless sensor networks using a chaotic genetic algorithm","volume":"8","author":"Wang","year":"2020","journal-title":"IEEE Access"},{"key":"ref_25","first-page":"1","article-title":"CGARP: Chaos genetic algorithm-based relay node placement for multifaceted heterogeneous wireless sensor networks","volume":"2022","author":"Banerjee","year":"2022","journal-title":"Innov. Syst. Softw. Eng."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"46","DOI":"10.1016\/j.advengsoft.2013.12.007","article-title":"Grey wolf optimizer","volume":"69","author":"Mirjalili","year":"2014","journal-title":"Adv. Eng. Softw."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"248","DOI":"10.1016\/j.procs.2017.12.034","article-title":"Performance Analysis of LEACH-GA over LEACH and LEACH-C in WSN","volume":"125","author":"Sivakumar","year":"2018","journal-title":"Procedia Comput. Sci."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"66013","DOI":"10.1109\/ACCESS.2020.2985495","article-title":"Fuzzy Clustering Algorithm for Enhancing Reliability and Network Lifetime of Wireless Sensor Networks","volume":"8","author":"Lata","year":"2020","journal-title":"IEEE Access"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/24\/13\/4406\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T15:11:24Z","timestamp":1760109084000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/24\/13\/4406"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,7,7]]},"references-count":28,"journal-issue":{"issue":"13","published-online":{"date-parts":[[2024,7]]}},"alternative-id":["s24134406"],"URL":"https:\/\/doi.org\/10.3390\/s24134406","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,7,7]]}}}