{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,26]],"date-time":"2026-03-26T15:31:46Z","timestamp":1774539106041,"version":"3.50.1"},"reference-count":48,"publisher":"MDPI AG","issue":"24","license":[{"start":{"date-parts":[[2021,12,17]],"date-time":"2021-12-17T00:00:00Z","timestamp":1639699200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Wireless sensor networks (WSNs) are one of the fundamental infrastructures for Internet of Things (IoTs) technology. Efficient energy consumption is one of the greatest challenges in WSNs because of its resource-constrained sensor nodes (SNs). Clustering techniques can significantly help resolve this issue and extend the network\u2019s lifespan. In clustering, WSN is divided into various clusters, and a cluster head (CH) is selected in each cluster. The selection of appropriate CHs highly influences the clustering technique, and poor cluster structures lead toward the early death of WSNs. In this paper, we propose an energy-efficient clustering and cluster head selection technique for next-generation wireless sensor networks (NG-WSNs). The proposed clustering approach is based on the midpoint technique, considering residual energy and distance among nodes. It distributes the sensors uniformly creating balanced clusters, and uses multihop communication for distant CHs to the base station (BS). We consider a four-layer hierarchical network composed of SNs, CHs, unmanned aerial vehicle (UAV), and BS. The UAV brings the advantage of flexibility and mobility; it shortens the communication range of sensors, which leads to an extended lifetime. Finally, a simulated annealing algorithm is applied for the optimal trajectory of the UAV according to the ground sensor network. The experimental results show that the proposed approach outperforms with respect to energy efficiency and network lifetime when compared with state-of-the-art techniques from recent literature.<\/jats:p>","DOI":"10.3390\/s21248445","type":"journal-article","created":{"date-parts":[[2021,12,20]],"date-time":"2021-12-20T02:40:32Z","timestamp":1639968032000},"page":"8445","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":44,"title":["Energy Efficient UAV Flight Path Model for Cluster Head Selection in Next-Generation Wireless Sensor Networks"],"prefix":"10.3390","volume":"21","author":[{"given":"Syed Kamran","family":"Haider","sequence":"first","affiliation":[{"name":"College of Internet of Things (IoT) Engineering, Hohai University, Changzhou 213001, China"},{"name":"Department of Electrical & Electronics Engineering, Beaconhouse International College, Islamabad 44000, Pakistan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Aimin","family":"Jiang","sequence":"additional","affiliation":[{"name":"College of Internet of Things (IoT) Engineering, Hohai University, Changzhou 213001, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8253-9709","authenticated-orcid":false,"given":"Ahmad","family":"Almogren","sequence":"additional","affiliation":[{"name":"Department of Computer Science, College of Computer and Information Sciences, King Saud University, Riyadh 11633, Saudi Arabia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5203-0621","authenticated-orcid":false,"given":"Ateeq Ur","family":"Rehman","sequence":"additional","affiliation":[{"name":"College of Internet of Things (IoT) Engineering, Hohai University, Changzhou 213001, China"},{"name":"Department of Electrical Engineering, Government College University, Lahore 54000, Pakistan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Abbas","family":"Ahmed","sequence":"additional","affiliation":[{"name":"Department of Electrical & Electronics Engineering, Beaconhouse International College, Islamabad 44000, Pakistan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wali Ullah","family":"Khan","sequence":"additional","affiliation":[{"name":"Interdisciplinary Centre for Security, Reliability and Trust (SnT), University of Luxembourg, 1855 Luxembourg, Luxembourg"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5320-1012","authenticated-orcid":false,"given":"Habib","family":"Hamam","sequence":"additional","affiliation":[{"name":"Faculty of Engineering, Uni de Moncton, Moncton, NB E1A 3E9, Canada"},{"name":"Spectrum of Knowledge Production & Skills Development, Sfax 3027, Tunisia"},{"name":"Department of Electrical and Electronic Engineering Science, School of Electrical Engineering, University of Johannesburg, Johannesburg 2006, South Africa"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,12,17]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"446","DOI":"10.1016\/j.future.2011.03.001","article-title":"Balancing energy consumption with mobile agents in wireless sensor networks","volume":"28","author":"Lin","year":"2012","journal-title":"Future Gener. Comput. Syst."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"114","DOI":"10.1109\/TCC.2015.2458272","article-title":"Energy efficient cooperative computing in mobile wireless sensor networks","volume":"6","author":"Sheng","year":"2015","journal-title":"IEEE Trans. Cloud Comput."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"3557","DOI":"10.1109\/TIE.2009.2039455","article-title":"Opportunities and challenges of wireless sensor networks in smart grid","volume":"57","author":"Gungor","year":"2010","journal-title":"IEEE Trans. Ind. Electron."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1007\/s11276-015-1133-7","article-title":"A review of industrial wireless networks in the context of industry 4.0","volume":"23","author":"Li","year":"2017","journal-title":"Wirel. Netw."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"56","DOI":"10.1109\/MNET.2013.6616116","article-title":"Cloud-enabled wireless body area networks for pervasive healthcare","volume":"27","author":"Wan","year":"2013","journal-title":"IEEE Netw."},{"key":"ref_6","first-page":"1","article-title":"Industrial technologies and applications for the Internet of Things","volume":"101","author":"Zhang","year":"2016","journal-title":"Comput. Netw. Int. J. Comput. Telecommun. Netw."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"43","DOI":"10.3991\/ijoe.v11i2.4366","article-title":"Design of a WSN System for Condition Monitoring of the Mechanical Equipment with Energy Harvesting","volume":"11","author":"Zheng","year":"2015","journal-title":"Int. J. Online Eng."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1109\/JETCAS.2013.2243032","article-title":"Design of a WSN platform for long-term environmental monitoring for IoT applications","volume":"3","author":"Lazarescu","year":"2013","journal-title":"IEEE J. Emerg. Sel. Top. Circuits Syst."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1550147717705614","DOI":"10.1177\/1550147717705614","article-title":"An optimization method to improve the performance of unmanned aerial vehicle wireless sensor networks","volume":"13","author":"Cao","year":"2017","journal-title":"Int. J. Distrib. Sens. Netw."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Ndiaye, M., Hancke, G.P., and Abu-Mahfouz, A.M. (2017). Software defined networking for improved wireless sensor network management: A survey. Sensors, 17.","DOI":"10.3390\/s17051031"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"188","DOI":"10.1016\/j.inffus.2018.03.005","article-title":"A comprehensive survey on the reliability of mobile wireless sensor networks: Taxonomy, challenges, and future directions","volume":"44","author":"Yue","year":"2018","journal-title":"Inf. Fusion"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"801","DOI":"10.1016\/j.sysarc.2013.05.022","article-title":"Large scale wireless sensor networks with multi-level dynamic key management scheme","volume":"59","author":"Sahingoz","year":"2013","journal-title":"J. Syst. Archit."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1146","DOI":"10.3390\/rs4051146","article-title":"Architecture and methods for innovative heterogeneous wireless sensor network applications","volume":"4","author":"Antonio","year":"2012","journal-title":"Remote Sens."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Awan, K.A., Din, I.U., Almogren, A., Kim, B.S., and Altameem, A. (2021). vTrust: An IoT-Enabled Trust-Based Secure Wireless Energy Sharing Mechanism for Vehicular Ad Hoc Networks. Sensors, 21.","DOI":"10.3390\/s21217363"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Almalki, A., Mohiuddin, I., AlMogren, A.S., and Ghoneim, A. (2020, January 8\u20139). Building a New Blueprint for Operating Workflow Efficiently. Proceedings of the 2020 International Conference on Decision Aid Sciences and Application (DASA), Online.","DOI":"10.1109\/DASA51403.2020.9317158"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"2741","DOI":"10.1109\/TWC.2015.2509069","article-title":"Energy-Efficient Optimal Power Allocation for Fading Cognitive Radio Channels: Ergodic Capacity, Outage Capacity, and Minimum-Rate Capacity","volume":"15","author":"Zhou","year":"2016","journal-title":"IEEE Trans. Wirel. Commun."},{"key":"ref_17","first-page":"3052","article-title":"Joint Offloading and Computation Energy Efficiency Maximization in a Mobile Edge Computing System","volume":"68","author":"Sun","year":"2019","journal-title":"IEEE Trans. Veh. Technol."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"3170","DOI":"10.1109\/TWC.2020.2970920","article-title":"Computation Efficiency Maximization in Wireless-Powered Mobile Edge Computing Networks","volume":"19","author":"Zhou","year":"2020","journal-title":"IEEE Trans. Wirel. Commun."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"2194","DOI":"10.1109\/LCOMM.2014.2381226","article-title":"Balancing energy consumption in heterogeneous wireless sensor networks using genetic algorithm","volume":"19","author":"Elhoseny","year":"2014","journal-title":"IEEE Commun. Lett."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"765","DOI":"10.1007\/s11277-015-2807-2","article-title":"EACHP: Energy aware clustering hierarchy protocol for large scale wireless sensor networks","volume":"85","author":"Barati","year":"2015","journal-title":"Wirel. Pers. Commun."},{"key":"ref_21","unstructured":"Zou, Y., and Chakrabarty, K. (April, January 30). Sensor deployment and target localization based on virtual forces. Proceedings of the Twenty-Second Annual Joint Conference of the IEEE Computer and Communications Societies, San Francisco, CA, USA."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1007\/s00530-013-0346-9","article-title":"Robust anonymous authentication protocol for health-care applications using wireless medical sensor networks","volume":"21","author":"He","year":"2015","journal-title":"Multimed. Syst."},{"key":"ref_23","unstructured":"Poduri, S., and Sukhatme, G.S. (May, January 26). Constrained coverage for mobile sensor networks. Proceedings of the IEEE International Conference on Robotics and Automation, New Orleans, LA, USA."},{"key":"ref_24","unstructured":"Heinzelman, W.R., Chandrakasan, A., and Balakrishnan, H. (2000, January 4\u20137). Energy- efficient communication protocol for wireless microsensor networks. Proceedings of the 33rd Annual Hawaii International Conference on System Sciences, Maui, HI, USA."},{"key":"ref_25","unstructured":"Chatterjee, M., Das, S.K., and Turgut, D. (December, January 27). An on-demand weighted clustering algorithm (WCA) for ad hoc networks. Proceedings of the IEEE Global Telecommunications Conference, San Francisco, CA, USA."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Khan, W.U., Li, X., Ihsan, A., Khan, M.A., Menon, V.G., and Ahmed, M. (2021). NOMA-Enabled Optimization Framework for Next-Generation Small-Cell IoV Networks Under Imperfect SIC Decoding. IEEE Trans. Intell. Transp. Syst.","DOI":"10.36227\/techrxiv.14716374.v1"},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Khan, W.U., Nguyen, T.N., Jameel, F., Jamshed, M.A., Pervaiz, H., Javed, M.A., and Jantti, R. (2021). Learning-Based Resource Allocation for Backscatter-Aided Vehicular Networks. IEEE Trans. Intell. Transp. Syst., 1\u201315. Available online: https:\/\/ieeexplore.ieee.org\/document\/9619857.","DOI":"10.36227\/techrxiv.16780234.v1"},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Khan, W.U., Javed, M.A., Nguyen, T.N., Khan, S., and Elhalawany, B.M. (2021). Energy-Efficient Resource Allocation for 6G Backscatter-Enabled NOMA IoV Networks. IEEE Trans. Intell. Transp. Syst., 1\u201311.","DOI":"10.36227\/techrxiv.15133902"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"1724","DOI":"10.1109\/TVT.2021.3056220","article-title":"Backscatter-Enabled Efficient V2X Communication With Non-Orthogonal Multiple Access","volume":"70","author":"Khan","year":"2021","journal-title":"IEEE Trans. Veh. Technol."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"18","DOI":"10.4236\/wsn.2012.41003","article-title":"Multiple parameter-based clustering (MPC): Prospective analysis for effective clustering in wireless sensor network (WSN) using K-means algorithm","volume":"4","author":"Khan","year":"2012","journal-title":"Wirel. Sens. Netw."},{"key":"ref_31","unstructured":"Park, G.Y., Kim, H., Jeong, H.W., and Youn, H.Y. (2013, January 25\u201328). A novel cluster head selection method based on K-means algorithm for energy efficient wireless sensor network. Proceedings of the IEEE 27th International Conference on Advanced Information Networking and Applications Workshops, Barcelona, Spain."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Haider, S.K., Jamshed, M.A., Jiang, A., and Pervaiz, H. (2019, January 20\u201324). An Energy Efficient Cluster-Heads Re-Usability Mechanism for Wireless Sensor Networks. Proceedings of the 2019 IEEE International Conference on Communications Workshops (ICC Workshops), Shanghai, China.","DOI":"10.1109\/ICCW.2019.8757015"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1155\/2016\/5040475","article-title":"Balanced cluster head selection based on modified k-means in a distributed wireless sensor network","volume":"12","author":"Periyasamy","year":"2016","journal-title":"Int. J. Distrib. Sens. Netw."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Haider, S.K., Jamshed, M.A., Jiang, A., Pervaiz, H., and Ni, Q. (2019, January 21\u201322). UAV-assisted Cluster-head Selection Mechanism for Wireless Sensor Network Applications. Proceedings of the IEEE 2019 UK\/ China Emerging Technologies (UCET), Glasgow, UK.","DOI":"10.1109\/UCET.2019.8881889"},{"key":"ref_35","first-page":"2409","article-title":"An enhanced K-means algorithm to improve the efficiency using normal distribution data points","volume":"2","author":"Napoleon","year":"2010","journal-title":"Int. J. Comput. Sci. Eng."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Chaari, R., Cheikhrouhou, O., Koub\u00e2a, A., Youssef, H., and Hmam, H. (2019, January 24\u201328). Towards a distributed computation offloading architecture for cloud robotics. Proceedings of the IEEE 15th International Wireless Communications & Mobile Computing Conference (IWCMC), Tangier, Morocco.","DOI":"10.1109\/IWCMC.2019.8766504"},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Xu, J., Solmaz, G., Rahmatizadeh, R., Turgut, D., and B\u00f6l\u00f6ni, L. (2015, January 26). Animal monitoring with unmanned aerial vehicle-aided wireless sensor networks. Proceedings of the 2015 IEEE 40th Conference on Local Computer Networks (LCN), Clearwater Beach, FL, USA.","DOI":"10.1109\/LCN.2015.7366291"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"4072","DOI":"10.3390\/s150204072","article-title":"Development and integration of a solar powered unmanned aerial vehicle and a wireless sensor network to monitor greenhouse gases","volume":"15","author":"Malaver","year":"2015","journal-title":"Sensors"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1016\/j.compag.2015.09.024","article-title":"Design of a low-cost wireless sensor network with UAV mobile node for agricultural applications","volume":"119","author":"Polo","year":"2015","journal-title":"Comput. Electron. Agric."},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Yousaf, A., Asif, R.M., Shakir, M., Rehman, A.U., Alassery, F., Hamam, H., and Cheikhrouhou, O. (2021). A Novel Machine Learning-Based Price Forecasting for Energy Management Systems. Sustainability, 13.","DOI":"10.3390\/su132212693"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"1142","DOI":"10.1007\/s11227-014-1161-6","article-title":"UAV-assisted data gathering in wireless sensor networks","volume":"70","author":"Dong","year":"2014","journal-title":"J. Supercomput."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"1187","DOI":"10.1007\/s11277-014-1924-7","article-title":"Low-energy adaptive unequal clustering protocol using fuzzy c-means in wireless sensor networks","volume":"79","author":"Dutta","year":"2014","journal-title":"Wirel. Pers. Commun."},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Nicolae, M., Popescu, D., and Dobrescu, R. (2015, January 7\u20139). UAV-WSN communication algorithm with increased energy autonomy. Proceedings of the IEEE 9th international symposium on advanced topics in electrical engineering (ATEE), Bucharest, Romania.","DOI":"10.1109\/ATEE.2015.7133937"},{"key":"ref_44","first-page":"30","article-title":"A localization based cooperative routing protocol for underwater wireless sensor networks","volume":"2017","author":"Javaid","year":"2017","journal-title":"Mob. Inf. Syst."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"140","DOI":"10.1016\/j.future.2018.11.014","article-title":"Application of reinforcement learning in UAV cluster task scheduling","volume":"95","author":"Yang","year":"2019","journal-title":"Future Gener. Comput. Syst."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"644","DOI":"10.1016\/j.future.2019.10.036","article-title":"A framework for topological based map building: A solution to autonomous robot navigation in smart cities","volume":"111","author":"Islam","year":"2020","journal-title":"Future Gener. Comput. Syst."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"680","DOI":"10.1109\/TWC.2019.2947670","article-title":"Residual Transceiver Hardware Impairments on Cooperative NOMA Networks","volume":"19","author":"Li","year":"2020","journal-title":"IEEE Trans. Wirel. Commun."},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"Li, X., Zheng, Y., Alshehri, M.D., Hai, L., Balasubramanian, V., Zeng, M., and Nie, G. (2021). Cognitive AmBC-NOMA IoV-MTS Networks with IQI: Reliability and Security Analysis. IEEE Trans. Intell. Transp. Syst., 1\u201312.","DOI":"10.1109\/TITS.2021.3113995"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/21\/24\/8445\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T07:50:58Z","timestamp":1760169058000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/21\/24\/8445"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,12,17]]},"references-count":48,"journal-issue":{"issue":"24","published-online":{"date-parts":[[2021,12]]}},"alternative-id":["s21248445"],"URL":"https:\/\/doi.org\/10.3390\/s21248445","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,12,17]]}}}