{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,29]],"date-time":"2026-07-29T14:33:41Z","timestamp":1785335621070,"version":"3.55.0"},"reference-count":47,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2023,12,29]],"date-time":"2023-12-29T00:00:00Z","timestamp":1703808000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Fundamental Research Funds for the Central Universities","award":["3102017zy026"],"award-info":[{"award-number":["3102017zy026"]}]},{"name":"Fundamental Research Funds for the Central Universities","award":["2023-JC-QN-0760"],"award-info":[{"award-number":["2023-JC-QN-0760"]}]},{"name":"Natural Science Basic Research Program of Shaanxi","award":["3102017zy026"],"award-info":[{"award-number":["3102017zy026"]}]},{"name":"Natural Science Basic Research Program of Shaanxi","award":["2023-JC-QN-0760"],"award-info":[{"award-number":["2023-JC-QN-0760"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Mobile crowdsensing (MCS), which is a grassroots sensing paradigm that utilizes the idea of crowdsourcing, has attracted the attention of academics. More and more researchers have devoted themselves to adopting MCS in space\u2013air\u2013ground\u2013sea integrated networks (SAGSINs). Given the dynamics of the environmental conditions in SAGSINs and the uncertainty of the sensing capabilities of mobile people, the quality and coverage of the sensed data change periodically. To address this issue, we propose a novel UAV-assisted cluster-based task allocation (UCTA) algorithm for MCS in SAGSINs in a two-stage process. We first introduce the edge nodes and establish a three-layer hierarchical system with UAV-assistance, called \u201cPlatform\u2013Edge Cluster\u2013Participants\u201d. Moreover, an edge-aided attribute-based cluster algorithm is designed, aiming at organizing tasks into clusters, which significantly diminishes both the communication overhead and computational complexity while enhancing the efficiency of task allocation. Subsequently, a greedy selection algorithm is proposed to select the final combination that performs the sensing task in each cluster. Extensive simulations are conducted comparing the developed algorithm with the other three benchmark algorithms, and the experimental results unequivocally endorse the superiority of our proposed UCTA algorithm.<\/jats:p>","DOI":"10.3390\/s24010208","type":"journal-article","created":{"date-parts":[[2023,12,29]],"date-time":"2023-12-29T11:19:21Z","timestamp":1703848761000},"page":"208","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["UAV-Assisted Cluster-Based Task Allocation for Mobile Crowdsensing in a Space\u2013Air\u2013Ground\u2013Sea Integrated Network"],"prefix":"10.3390","volume":"24","author":[{"given":"Yang","family":"Liu","sequence":"first","affiliation":[{"name":"School of Electronics and Information, Northwestern Polytechnical University, Xi\u2019an 710129, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yong","family":"Li","sequence":"additional","affiliation":[{"name":"School of Electronics and Information, Northwestern Polytechnical University, Xi\u2019an 710129, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0874-9927","authenticated-orcid":false,"given":"Wei","family":"Cheng","sequence":"additional","affiliation":[{"name":"School of Electronics and Information, Northwestern Polytechnical University, Xi\u2019an 710129, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7989-4937","authenticated-orcid":false,"given":"Weiguang","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Information Engineering, Henan University of Science and Technology, Luoyang 471000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8546-9729","authenticated-orcid":false,"given":"Junhua","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Electronic Engineering, Xi\u2019an University of Posts and Telecommunications, Xi\u2019an 710121, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,12,29]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Pang, Y., Wang, D., Wang, D., Guan, L., Zhang, C., and Zhang, L. (2020, January 18\u201323). A space-air-ground integrated network assisted maritime communication network based on mobile edge computing. Proceedings of the 2020 IEEE World Congress on Services (SERVICES), Beijing, China.","DOI":"10.1109\/SERVICES48979.2020.00060"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"53","DOI":"10.1109\/COMST.2021.3131332","article-title":"A survey on space-air-ground-sea integrated network security in 6G","volume":"24","author":"Guo","year":"2021","journal-title":"IEEE Commun. Surv. Tutor."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/2818183","article-title":"Mobile crowd sensing and computing: The review of an emerging human-powered sensing paradigm","volume":"48","author":"Guo","year":"2015","journal-title":"ACM Comput. Surv. (CSUR)"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"28","DOI":"10.1109\/MVT.2019.2921208","article-title":"6G wireless networks: Vision, requirements, architecture, and key technologies","volume":"14","author":"Zhang","year":"2019","journal-title":"IEEE Veh. Technol. Mag."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Wang, D., Wu, M., Chakraborty, C., Min, L., He, Y., and Guduri, M. (2023). Covert communications in air-ground integrated urban sensing networks enhanced by federated learning. IEEE Sens. J.","DOI":"10.1109\/JSEN.2023.3322784"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"42","DOI":"10.1109\/MCOM.2014.6871668","article-title":"4W1H in mobile crowd sensing","volume":"52","author":"Zhang","year":"2014","journal-title":"IEEE Commun. Mag."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1749","DOI":"10.1109\/JIOT.2018.2815982","article-title":"Task allocation in spatial crowdsourcing: Current state and future directions","volume":"5","author":"Guo","year":"2018","journal-title":"IEEE Internet Things J."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"78406","DOI":"10.1109\/ACCESS.2019.2896226","article-title":"A survey of task allocation: Contrastive perspectives from wireless sensor networks and mobile crowdsensing","volume":"7","author":"Guo","year":"2019","journal-title":"IEEE Access"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Wang, Y., Sun, G., and Ding, X. (2019). Coverage-balancing user selection in mobile crowd sensing with budget constraint. Sensors, 19.","DOI":"10.3390\/s19102371"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Van Anh Duong, D., and Yoon, S. (2022). A Human Location Prediction-Based Routing Protocol in Mobile Crowdsensing-Based Urban Sensor Networks. Appl. Sci., 12.","DOI":"10.3390\/app12083898"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Hirth, M., Seufert, M., Lange, S., Meixner, M., and Tran-Gia, P. (2021). Performance evaluation of hybrid crowdsensing and fixed sensor systems for event detection in urban environments. Sensors, 21.","DOI":"10.3390\/s21175880"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"4201","DOI":"10.1109\/TMC.2021.3079984","article-title":"Blockchain-enabled intelligent transportation systems: A distributed crowdsensing framework","volume":"21","author":"Ning","year":"2021","journal-title":"IEEE Trans. Mob. Comput."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"9503","DOI":"10.1109\/TII.2022.3228935","article-title":"Multi-Task-Oriented Collaborative Crowdsensing Based on Reinforcement Learning and Blockchain for Intelligent Transportation System","volume":"19","author":"Li","year":"2022","journal-title":"IEEE Trans. Ind. Inform."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"2038","DOI":"10.1109\/TGCN.2023.3245098","article-title":"A V2I and V2V collaboration framework to support emergency communications in ABS-aided Internet of Vehicles","volume":"7","author":"He","year":"2023","journal-title":"IEEE Trans. Green Commun. Netw."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"76","DOI":"10.1145\/3481621","article-title":"Crowdsensing 2.0","volume":"64","author":"Yu","year":"2021","journal-title":"Commun. ACM"},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Chen, J., and Yang, J. (2019). Maximizing coverage quality with budget constrained in mobile crowd-sensing network for environmental monitoring applications. Sensors, 19.","DOI":"10.3390\/s19102399"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Wang, Y., Wang, M., Meng, L., Zhang, Q., Tong, X., and Cai, Z. (2021, January 23\u201325). New crowd sensing computing in space-air-ground integrated networks. Proceedings of the 2021 International Conference on Space-Air-Ground Computing (SAGC), Huizhou, China.","DOI":"10.1109\/SAGC52752.2021.00031"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"766","DOI":"10.1109\/TNSE.2018.2830307","article-title":"A private and efficient mechanism for data uploading in smart cyber-physical systems","volume":"7","author":"Cai","year":"2018","journal-title":"IEEE Trans. Netw. Sci. Eng."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Moroni, D., Pieri, G., Reggiannini, M., and Tampucci, M. (2022, January 21\u201325). A mobile crowdsensing app for improved maritime security and awareness. Proceedings of the 2022 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops), Pisa, Italy.","DOI":"10.1109\/PerComWorkshops53856.2022.9767516"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"3790","DOI":"10.1109\/TMC.2022.3147871","article-title":"A UAV-assisted multi-task allocation method for mobile crowd sensing","volume":"22","author":"Gao","year":"2022","journal-title":"IEEE Trans. Mob. Comput."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"3747","DOI":"10.1109\/JIOT.2018.2864341","article-title":"Task allocation in mobile crowd sensing: State-of-the-art and future opportunities","volume":"5","author":"Wang","year":"2018","journal-title":"IEEE Internet Things J."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Li, Z., Liu, H., and Wang, R. (2019). Service benefit aware multi-task assignment strategy for mobile crowd sensing. Sensors, 19.","DOI":"10.3390\/s19214666"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1029","DOI":"10.1109\/JIOT.2018.2866973","article-title":"Location-dependent task allocation for mobile crowdsensing with clustering effect","volume":"6","author":"Tao","year":"2018","journal-title":"IEEE Internet Things J."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"3194","DOI":"10.1109\/TMC.2020.2997280","article-title":"QoS-based budget constrained stable task assignment in mobile crowdsensing","volume":"20","author":"Yucel","year":"2020","journal-title":"IEEE Trans. Mob. Comput."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Zhang, J., Zhang, Y., Wu, H., and Li, W. (2022). An Ordered Submodularity-Based Budget-Feasible Mechanism for Opportunistic Mobile Crowdsensing Task Allocation and Pricing. IEEE Trans. Mob. Comput.","DOI":"10.1109\/TMC.2022.3232513"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"2476","DOI":"10.1109\/TII.2021.3094527","article-title":"OPAT: Optimized allocation of time-dependent tasks for mobile crowdsensing","volume":"18","author":"Huang","year":"2021","journal-title":"IEEE Trans. Ind. Inform."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"3439","DOI":"10.1109\/TMC.2020.3000234","article-title":"Stable task assignment for mobile crowdsensing with budget constraint","volume":"20","author":"Dai","year":"2020","journal-title":"IEEE Trans. Mob. Comput."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"22305","DOI":"10.1109\/JIOT.2023.3303413","article-title":"A NOMA and MRC enabled framework in drone-relayed vehicular networks: Height\/trajectory optimization and performance analysis","volume":"24","author":"He","year":"2023","journal-title":"IEEE Internet Things J."},{"key":"ref_29","first-page":"52","article-title":"Using context annotated mobility profiles to recruit data collectors in participatory sensing","volume":"Volume 5561","author":"Choudhury","year":"2009","journal-title":"LoCA 2009: Location and Context Awareness"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"769","DOI":"10.1109\/TSC.2017.2725835","article-title":"A crowd-sensing framework for allocation of time-constrained and location-based tasks","volume":"13","author":"Estrada","year":"2017","journal-title":"IEEE Trans. Serv. Comput."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"2101","DOI":"10.1109\/TMC.2018.2793908","article-title":"Multi-task allocation in mobile crowd sensing with individual task quality assurance","volume":"17","author":"Wang","year":"2018","journal-title":"IEEE Trans. Mob. Comput."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"7407","DOI":"10.1109\/JIOT.2020.2984826","article-title":"Coverage-oriented task assignment for mobile crowdsensing","volume":"7","author":"Song","year":"2020","journal-title":"IEEE Internet Things J."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1262","DOI":"10.1109\/JSAC.2019.2904353","article-title":"Energy-efficient distributed mobile crowd sensing: A deep learning approach","volume":"37","author":"Liu","year":"2019","journal-title":"IEEE J. Sel. Areas Commun."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1274","DOI":"10.1109\/TMC.2019.2908171","article-title":"Distributed energy-efficient multi-UAV navigation for long-term communication coverage by deep reinforcement learning","volume":"19","author":"Liu","year":"2019","journal-title":"IEEE Trans. Mob. Comput."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"1070","DOI":"10.1109\/TVT.2019.2949634","article-title":"Social-aware UAV-assisted mobile crowd sensing in stochastic and dynamic environments for disaster relief networks","volume":"69","author":"Wang","year":"2019","journal-title":"IEEE Trans. Veh. Technol."},{"key":"ref_36","first-page":"2025","article-title":"Energy-Efficient 3D Data Collection for Multi-UAV Assisted Mobile Crowdsensing","volume":"72","author":"Fu","year":"2022","journal-title":"IEEE Trans. Comput."},{"key":"ref_37","unstructured":"Cardei, M., Thai, M.T., Li, Y., and Wu, W. (2005, January 13\u201317). Energy-efficient target coverage in wireless sensor networks. Proceedings of the IEEE 24th Annual Joint Conference of the IEEE Computer and Communications Societies, Miami, FL, USA."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Liu, Y., Li, Y., Cheng, W., Wang, W., and Yang, J. (2023). A Reputation-Based Collaborative User Recruitment Algorithm in Edge-Aided Mobile Crowdsensing. Appl. Sci., 13.","DOI":"10.3390\/app13106040"},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Shi, S., Cui, J., Jiang, Z., Yan, Z., Xing, G., Niu, J., and Ouyang, Z. (2022, January 17\u201321). VIPS: Real-time perception fusion for infrastructure-assisted autonomous driving. Proceedings of the 28th Annual International Conference on Mobile Computing and Networking, Sydney, NSW, Australia.","DOI":"10.1145\/3495243.3560539"},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Gehlot, A., Alshamrani, S.S., Singh, R., Rashid, M., Akram, S., AIGhamdi, A., and Albogamy, F. (2021). Internet of things and long-range-based smart lampposts for illuminating smart cities. Sustainability, 13.","DOI":"10.3390\/su13116398"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"2639","DOI":"10.1109\/TMC.2016.2626434","article-title":"Smart base station-assisted partial-flow device-to-device offloading system for video streaming services","volume":"16","author":"Park","year":"2016","journal-title":"IEEE Trans. Mob. Comput."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"100207","DOI":"10.1016\/j.iot.2020.100207","article-title":"Internet of smart-cameras for traffic lights optimization in smart cities","volume":"11","author":"Tchuitcheu","year":"2020","journal-title":"Internet Things"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"392","DOI":"10.1109\/THMS.2016.2599489","article-title":"ActiveCrowd: A framework for optimized multitask allocation in mobile crowdsensing systems","volume":"47","author":"Guo","year":"2016","journal-title":"IEEE Trans. Hum.-Mach. Syst."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"4579","DOI":"10.1109\/JIOT.2020.3027057","article-title":"From centralized management to edge collaboration: A privacy-preserving task assignment framework for mobile crowdsensing","volume":"8","author":"Wu","year":"2020","journal-title":"IEEE Internet Things J."},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Xu, S., Zhang, J., Meng, S., and Xu, J. (2021). Task allocation for unmanned aerial vehicles in mobile crowdsensing. Wirel. Netw., 1\u201313.","DOI":"10.1007\/s11276-021-02638-7"},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"3490","DOI":"10.1109\/ACCESS.2017.2671678","article-title":"Crowdsensim: A simulation platform for mobile crowdsensing in realistic urban environments","volume":"5","author":"Fiandrino","year":"2017","journal-title":"IEEE Access"},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Montori, F., Cortesi, E., Bedogni, L., Capponi, A., Fiandrino, C., and Bononi, L. (2019, January 25\u201329). Crowdsensim 2.0: A stateful simulation platform for mobile crowdsensing in smart cities. Proceedings of the 22nd International ACM Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems, Miami Beach, FL, USA.","DOI":"10.1145\/3345768.3355929"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/24\/1\/208\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T21:44:22Z","timestamp":1760132662000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/24\/1\/208"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,12,29]]},"references-count":47,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2024,1]]}},"alternative-id":["s24010208"],"URL":"https:\/\/doi.org\/10.3390\/s24010208","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,12,29]]}}}