{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,6]],"date-time":"2026-07-06T23:28:23Z","timestamp":1783380503347,"version":"3.54.6"},"reference-count":25,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2022,9,27]],"date-time":"2022-09-27T00:00:00Z","timestamp":1664236800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"science and technology research project of the Henan province","award":["222102240014"],"award-info":[{"award-number":["222102240014"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>With the continuous development of Unmanned Aerial Vehicle (UAV) technology, UAVs are widely used in military and civilian fields. Multi-UAV networks are often referred to as flying ad hoc networks (FANET). Dividing multiple UAVs into clusters for management can reduce energy consumption, maximize network lifetime, and enhance network scalability to a certain extent, so UAV clustering is an important direction for UAV network applications. However, UAVs have the characteristics of limited energy resources and high mobility, which bring challenges to UAV cluster communication networking. Therefore, this paper proposes a clustering scheme for UAV clusters based on the binary whale optimization (BWOA) algorithm. First, the optimal number of clusters in the network is calculated based on the network bandwidth and node coverage constraints. Then, the cluster heads are selected based on the optimal number of clusters using the BWOA algorithm, and the clusters are divided based on the distance. Finally, the cluster maintenance strategy is set to achieve efficient maintenance of clusters. The experimental simulation results show that the scheme has better performance in terms of energy consumption and network lifetime compared with the BPSO and K-means-based schemes.<\/jats:p>","DOI":"10.3390\/e24101366","type":"journal-article","created":{"date-parts":[[2022,9,27]],"date-time":"2022-09-27T23:12:12Z","timestamp":1664320332000},"page":"1366","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":17,"title":["A Clustering Scheme Based on the Binary Whale Optimization Algorithm in FANET"],"prefix":"10.3390","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8606-793X","authenticated-orcid":false,"given":"Yonghang","family":"Yan","sequence":"first","affiliation":[{"name":"School of Computer and Information Engineering, Henan University, Kaifeng 475004, China"},{"name":"Henan Province Engineering Research Center of Spatial Information Processing, Henan University, Kaifeng 475004, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4241-0553","authenticated-orcid":false,"given":"Xuewen","family":"Xia","sequence":"additional","affiliation":[{"name":"School of Computer and Information Engineering, Henan University, Kaifeng 475004, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lingli","family":"Zhang","sequence":"additional","affiliation":[{"name":"Beijing Aerospace Automatic Control Institute, Beijing 100854, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1472-5718","authenticated-orcid":false,"given":"Zhijia","family":"Li","sequence":"additional","affiliation":[{"name":"School of Computer and Information Engineering, Henan University, Kaifeng 475004, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8238-5922","authenticated-orcid":false,"given":"Chunbin","family":"Qin","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence, Henan University, Kaifeng 475004, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,9,27]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1071","DOI":"10.1109\/COMST.2020.2982452","article-title":"Routing in Flying Ad Hoc Networks: A Comprehensive Survey","volume":"22","author":"Lakew","year":"2020","journal-title":"IEEE Commun. Surv. Tutor."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1109\/MWC.2018.1800160","article-title":"UAV-assisted emergency networks in disasters","volume":"26","author":"Zhao","year":"2019","journal-title":"IEEE Wirel. Commun."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Qu, Y., Zhang, F., Wu, X., and Xiao, B. (2019). Cooperative geometric localization for a ground target based on the relative distances by multiple UAVs. Sci. China Inf. Sci., 62.","DOI":"10.1007\/s11432-018-9579-3"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1109\/MSPEC.2017.7802742","article-title":"Air traffic control for delivery drones [Top Tech 2017]","volume":"54","author":"Schneider","year":"2017","journal-title":"IEEE Spectr."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"33","DOI":"10.5055\/jem.0496","article-title":"Unmanned aerial systems (UAS) in urban search and rescue-methodology, capacity development, and integration","volume":"19","author":"Braverman","year":"2021","journal-title":"J. Emerg. Manag."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Aadil, F., Raza, A., Khan, M.F., Maqsood, M., Mehmood, I., and Rho, S. (2018). Energy aware Cluster based Routing in Flying Ad-hoc Networks. Sensors, 18.","DOI":"10.3390\/s18051413"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"106364","DOI":"10.1109\/ACCESS.2020.3000222","article-title":"Mobility and Location-aware Stable Clustering Scheme for UAV Networks","volume":"8","author":"Bhandari","year":"2020","journal-title":"IEEE Access"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Medani, K., Guemer, H., Aliouat, Z., and Harous, S. (2021, January 13\u201315). Area Division Cluster-based Algorithm for Data Collection over UAV Networks. Proceedings of the 2021 IEEE International Conference on Electro Information Technology (EIT), Mt. Pleasant, MI, USA.","DOI":"10.1109\/EIT51626.2021.9491898"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Yang, X.W., Yu, T.Q., Chen, Z.Y., Yang, J.F., Hu, J.L., and Wu, Y.R. (2022). An Improved Weighted and Location-Based Clustering Scheme for Flying Ad Hoc Networks. Sensors, 22.","DOI":"10.3390\/s22093236"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"31446","DOI":"10.1109\/ACCESS.2019.2902940","article-title":"BICSF: Bio-Inspired Clustering Scheme for FANETs","volume":"7","author":"Khan","year":"2019","journal-title":"IEEE Access"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"76","DOI":"10.1007\/s11432-019-2984-7","article-title":"Intelligent cluster routing scheme for flying ad hoc networks","volume":"64","author":"Khan","year":"2021","journal-title":"Sci. China Inf. Sci."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"8958","DOI":"10.1109\/JIOT.2019.2925567","article-title":"Localization and Clustering Based on Swarm Intelligence in UAV Networks for Emergency Communications","volume":"6","author":"Arafat","year":"2019","journal-title":"IEEE Internet Things J."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"18649","DOI":"10.1109\/ACCESS.2021.3053605","article-title":"Bio-Inspired Approaches for Energy-Efficient Localization and Clustering in UAV Networks for Monitoring Wildfires in Remote Areas","volume":"9","author":"Arafat","year":"2021","journal-title":"IEEE Access"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"158574","DOI":"10.1109\/ACCESS.2021.3130417","article-title":"A Dynamic Clustering Mechanism with Load-Balancing for Flying Ad Hoc Networks","volume":"9","author":"Asaamoning","year":"2021","journal-title":"IEEE Access"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Ghazzai, H., Ghorbel, M.B., Kadri, A., and Hossain, M.J. (2017, January 21\u201325). Energy efficient 3D positioning of micro unmanned aerial vehicles for underlay cognitive radio systems. Proceedings of the 2017 IEEE International Conference on Communications (ICC), Paris, France.","DOI":"10.1109\/ICC.2017.7996485"},{"key":"ref_16","unstructured":"Heinzelman, W.R., Chandrakasan, A., and Balakrishnan, H. (2000, January 7). Energy-efficient communication protocol for wireless microsensor networks. Proceedings of the Hawaii International Conference on System Sciences, Maui, HI, USA."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"51","DOI":"10.1016\/j.advengsoft.2016.01.008","article-title":"The Whale Optimization Algorithm","volume":"95","author":"Mirjalili","year":"2016","journal-title":"Adv. Eng. Softw."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"149814","DOI":"10.1109\/ACCESS.2021.3124710","article-title":"Overview on Binary Optimization Using Swarm-Inspired Algorithms","volume":"9","author":"Macedo","year":"2021","journal-title":"IEEE Access"},{"key":"ref_19","first-page":"293","article-title":"Binary whale optimization algorithm and its application to unit commitment problem","volume":"2","author":"Reddy","year":"2018","journal-title":"Neural Comput. Appl."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"4285","DOI":"10.1109\/TVT.2020.2973294","article-title":"Whale Optimization Algorithm with Applications to Resource Allocation in Wireless Networks","volume":"69","author":"Pham","year":"2020","journal-title":"IEEE Trans. Veh. Technol."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"495","DOI":"10.1007\/s13042-017-0731-3","article-title":"A modified nature inspired meta-heuristic whale optimization algorithm for solving 0\u20131 knapsack problem","volume":"10","author":"Basset","year":"2019","journal-title":"Int. J. Mach. Learn. Cybern."},{"key":"ref_22","first-page":"147","article-title":"Clustering Algrothrim of WSN Based on Binary Particle Swarm Optimization","volume":"32","author":"Cao","year":"2015","journal-title":"Microelectron. Comput."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"170019","DOI":"10.1109\/ACCESS.2019.2955993","article-title":"Energy-Efficient Routing in WSN: A Centralized Cluster-Based Approach via Grey Wolf Optimizer","volume":"7","author":"Daneshvar","year":"2019","journal-title":"IEEE Access"},{"key":"ref_24","first-page":"2670","article-title":"Adaptive K-means clustering for flying ad-hoc networks","volume":"14","author":"Raza","year":"2020","journal-title":"KSII Trans. Internet Inf. Syst."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"6180","DOI":"10.1109\/TWC.2014.2337315","article-title":"Performance analysis of group-synchronized DCF for dense IEEE 802.11 networks","volume":"13","author":"Zheng","year":"2014","journal-title":"IEEE Trans. Wirel. Commun."}],"container-title":["Entropy"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1099-4300\/24\/10\/1366\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T00:40:13Z","timestamp":1760143213000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1099-4300\/24\/10\/1366"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,9,27]]},"references-count":25,"journal-issue":{"issue":"10","published-online":{"date-parts":[[2022,10]]}},"alternative-id":["e24101366"],"URL":"https:\/\/doi.org\/10.3390\/e24101366","relation":{},"ISSN":["1099-4300"],"issn-type":[{"value":"1099-4300","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,9,27]]}}}