{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,3]],"date-time":"2026-04-03T15:12:58Z","timestamp":1775229178807,"version":"3.50.1"},"reference-count":46,"publisher":"Association for Computing Machinery (ACM)","issue":"1","license":[{"start":{"date-parts":[[2025,2,11]],"date-time":"2025-02-11T00:00:00Z","timestamp":1739232000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["62202055 and 62202016"],"award-info":[{"award-number":["62202055 and 62202016"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Start-up Fund from Beijing Normal University","award":["312200502510"],"award-info":[{"award-number":["312200502510"]}]},{"name":"Internal Fund from BNU-HKBU United International College","award":["UICR0400003-24"],"award-info":[{"award-number":["UICR0400003-24"]}]},{"name":"Project of Young Innovative Talents of Guangdong Education Department","award":["2022KQNCX102"],"award-info":[{"award-number":["2022KQNCX102"]}]},{"name":"National Science Foundation","award":["1907472 and 1822985"],"award-info":[{"award-number":["1907472 and 1822985"]}]},{"name":"Interdisciplinary Intelligence SuperComputer Center, Beijing Normal University"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Internet Technol."],"published-print":{"date-parts":[[2025,2,28]]},"abstract":"<jats:p>Spatiotemporal Mobile CrowdSourcing (MCS) is a new intelligent sensing paradigm for large-scale data acquisition where requesters can recruit a crowd of workers to perform data collection tasks. How to recruit suitable workers in a dynamic environment to maximize platform utility is a key issue and has become a research hotspot. Many past studies have made great efforts in this regard, but most of them either assume that the worker quality is known in advance or ignore the limitations of workers\u2019 short-term ability to provide resources. In this article, we consider a platform-centered online spatiotemporal MCS system where mobile workers have both long-term and short-term constraints for providing resources, and their quality is unknown to the platform, while the platform has a long-term budget constraint for recruiting workers. We aim to find an online worker scheduling scheme to maximize the platform\u2019s long-term utility without violating the constraints of both workers and the platform. To address this problem, we first transform the long-term utility maximization problem into a real-time utility maximization problem by leveraging the Lyapunov optimization, then design algorithms based on the Upper Confidence Bound (UCB) and Markov approximation to solve each real-time utility maximization problem with unknown worker quality. We demonstrate that our UCB-based algorithm has a sublinear regret and prove that our proposed framework has a performance guarantee for the addressed problem. Finally, we evaluate our design through numerical simulation experiments, and the results demonstrate the effectiveness of our algorithm.<\/jats:p>","DOI":"10.1145\/3708893","type":"journal-article","created":{"date-parts":[[2024,12,18]],"date-time":"2024-12-18T10:55:36Z","timestamp":1734519336000},"page":"1-25","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":4,"title":["Online Worker Scheduling for Maximizing Long-Term Utility in Crowdsourcing with Unknown Quality"],"prefix":"10.1145","volume":"25","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-8300-5218","authenticated-orcid":false,"given":"Jiajun","family":"Wang","sequence":"first","affiliation":[{"name":"College of Computer Science, Beijing University of Technology, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0676-7128","authenticated-orcid":false,"given":"Pengfei","family":"Lin","sequence":"additional","affiliation":[{"name":"College of Computer Science, Beijing University of Technology, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8866-4941","authenticated-orcid":false,"given":"Xingjian","family":"Ding","sequence":"additional","affiliation":[{"name":"College of Computer Science, Beijing University of Technology, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0994-3297","authenticated-orcid":false,"given":"Jianxiong","family":"Guo","sequence":"additional","affiliation":[{"name":"Advanced Institute of Natural Sciences, Beijing Normal University, Zhuhai, China and Guangdong Key Lab of AI and Multi-Modal Data Processing, BNU-HKBU United International College, Zhuhai, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9375-4818","authenticated-orcid":false,"given":"Zhiqing","family":"Tang","sequence":"additional","affiliation":[{"name":"Advanced Institute of Natural Sciences, Beijing Normal University, Zhuhai, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7748-5427","authenticated-orcid":false,"given":"Deying","family":"Li","sequence":"additional","affiliation":[{"name":"School of Information, Renmin University of China, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8747-6340","authenticated-orcid":false,"given":"Weili","family":"Wu","sequence":"additional","affiliation":[{"name":"Department of Computer Science, The University of Texas at Dallas, Richardson, United States"}]}],"member":"320","published-online":{"date-parts":[[2025,2,11]]},"reference":[{"key":"e_1_3_1_2_2","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9780511804441"},{"key":"e_1_3_1_3_2","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2022.3227618"},{"key":"e_1_3_1_4_2","doi-asserted-by":"publisher","DOI":"10.1137\/S0097539700382820"},{"key":"e_1_3_1_5_2","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.2013.2268923"},{"key":"e_1_3_1_6_2","doi-asserted-by":"publisher","DOI":"10.1109\/TNSE.2022.3163925"},{"key":"e_1_3_1_7_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2020.106781"},{"key":"e_1_3_1_8_2","doi-asserted-by":"publisher","DOI":"10.1109\/TDSC.2024.3428405"},{"issue":"11","key":"e_1_3_1_9_2","first-page":"3895","article-title":"Budgeted unknown worker recruitment for heterogeneous crowdsensing using CMAB","volume":"21","author":"Gao Guoju","year":"2022","unstructured":"Guoju Gao, He Huang, Mingjun Xiao et\u00a0al. 2022. Budgeted unknown worker recruitment for heterogeneous crowdsensing using CMAB. IEEE Trans. Mobile Comput. 21, 11 (Nov.2022), 3895\u20133911.","journal-title":"IEEE Trans. Mobile Comput."},{"key":"e_1_3_1_10_2","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2022.3147871"},{"key":"e_1_3_1_11_2","doi-asserted-by":"publisher","DOI":"10.1109\/COMST.2022.3187138"},{"issue":"2","key":"e_1_3_1_12_2","doi-asserted-by":"crossref","first-page":"1939","DOI":"10.1109\/JIOT.2023.3284477","article-title":"Gather or scatter: Stackelberg-game-based task decision for blockchain-assisted socially aware crowdsensing framework","volume":"11","author":"Huang Sijie","year":"2024","unstructured":"Sijie Huang, Guoju Gao, He Huang et\u00a0al. 2024. Gather or scatter: Stackelberg-game-based task decision for blockchain-assisted socially aware crowdsensing framework. IEEE Internet Things J. 11, 2 (Jan.2024), 1939\u20131951.","journal-title":"IEEE Internet Things J."},{"key":"e_1_3_1_13_2","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2022.3150432"},{"issue":"1","key":"e_1_3_1_14_2","doi-asserted-by":"crossref","first-page":"4804231","DOI":"10.1155\/2022\/4804231","article-title":"User recruitment algorithm for maximizing quality under limited budget in mobile crowdsensing","volume":"2022","author":"Jiang W.","year":"2022","unstructured":"W. Jiang, P. Chen, W. Zhang et\u00a0al. 2022. User recruitment algorithm for maximizing quality under limited budget in mobile crowdsensing. Discrete Dynam. Nature Soc. 2022, 1 (2022), 4804231.","journal-title":"Discrete Dynam. Nature Soc."},{"key":"e_1_3_1_15_2","doi-asserted-by":"publisher","DOI":"10.1109\/TNET.2024.3355169"},{"key":"e_1_3_1_16_2","article-title":"Mobile crowdsensing ecosystem with combinatorial multi-armed bandit-based dynamic truth discovery","author":"Liu Jia","year":"2024","unstructured":"Jia Liu, Jianbo Shao, Min Sheng et\u00a0al. 2024. Mobile crowdsensing ecosystem with combinatorial multi-armed bandit-based dynamic truth discovery. IEEE Trans. Mobile Comput. 23, 12 (2024), 13095\u201313113.","journal-title":"IEEE Trans. Mobile Comput."},{"key":"e_1_3_1_17_2","article-title":"Conscious task recommendation via cognitive reasoning computing in mobile crowd sensing","author":"Liu Jia","year":"2024","unstructured":"Jia Liu, Jian Wang, and Guosheng Zhao. 2024. Conscious task recommendation via cognitive reasoning computing in mobile crowd sensing. ACM Trans. Internet Technol. 24, 4 (2024), 18:1\u201318:25.","journal-title":"ACM Trans. Internet Technol."},{"key":"e_1_3_1_18_2","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2024.3364239"},{"key":"e_1_3_1_19_2","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2021.3076811"},{"key":"e_1_3_1_20_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.aei.2021.101494"},{"key":"e_1_3_1_21_2","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2023.3236679"},{"key":"e_1_3_1_22_2","doi-asserted-by":"publisher","DOI":"10.1109\/TSC.2024.3433541"},{"key":"e_1_3_1_23_2","volume-title":"Stochastic Network Optimization with Application to Communication and Queueing Systems","author":"Neely Michael","year":"2022","unstructured":"Michael Neely. 2022. Stochastic Network Optimization with Application to Communication and Queueing Systems. Springer Nature."},{"key":"e_1_3_1_24_2","doi-asserted-by":"publisher","DOI":"10.1109\/JSAC.2018.2869954"},{"key":"e_1_3_1_25_2","doi-asserted-by":"publisher","DOI":"10.1007\/s12083-023-01454-4"},{"issue":"19","key":"e_1_3_1_26_2","doi-asserted-by":"crossref","first-page":"16881","DOI":"10.1109\/JIOT.2023.3274753","article-title":"A multiplatform-cooperation-based task assignment mechanism for mobile crowdsensing","volume":"10","author":"Peng Shuo","year":"2023","unstructured":"Shuo Peng, Baoxian Zhang, Yan Yan et\u00a0al. 2023. A multiplatform-cooperation-based task assignment mechanism for mobile crowdsensing. IEEE Internet Things J. 10, 19 (Oct.2023), 16881\u201316894.","journal-title":"IEEE Internet Things J."},{"key":"e_1_3_1_27_2","doi-asserted-by":"publisher","DOI":"10.1109\/9.317122"},{"key":"e_1_3_1_28_2","first-page":"1","volume-title":"Proceedings of the International Conference on Computer Communications and Networks (ICCCN\u201922)","author":"Sima Qinghua","year":"2022","unstructured":"Qinghua Sima, Guoju Gao, He Huang et\u00a0al. 2022. Multi-armed bandits based task selection of a mobile crowdsensing worker. In Proceedings of the International Conference on Computer Communications and Networks (ICCCN\u201922). IEEE, 1\u201310."},{"key":"e_1_3_1_29_2","first-page":"3086","volume-title":"Proceedings of the International Conference on Artificial Intelligence and Statistics","author":"Simchi-Levi David","year":"2023","unstructured":"David Simchi-Levi and Chonghuan Wang. 2023. Multi-armed bandit experimental design: Online decision-making and adaptive inference. In Proceedings of the International Conference on Artificial Intelligence and Statistics. PMLR, 3086\u20133097."},{"key":"e_1_3_1_30_2","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2020.2984826"},{"issue":"8","key":"e_1_3_1_31_2","article-title":"Q-BLPP: A quality-enabled bilateral location privacy-preserving service construction scheme in mobile crowd sensing","volume":"14","author":"Tang Jianheng","year":"2024","unstructured":"Jianheng Tang, Yishuo Cai, Saiqin Long et\u00a0al. 2024. Q-BLPP: A quality-enabled bilateral location privacy-preserving service construction scheme in mobile crowd sensing. IEEE Trans. Serv. Comput. 14, 8 (Nov.2024).","journal-title":"IEEE Trans. Serv. Comput."},{"key":"e_1_3_1_32_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2023.119444"},{"key":"e_1_3_1_33_2","first-page":"517","volume-title":"Proceedings of the IEEE 36th International Conference on Data Engineering (ICDE\u201920)","author":"Tao Qian","year":"2020","unstructured":"Qian Tao, Yongxin Tong, Zimu Zhou, Yexuan Shi, Lei Chen, and Ke Xu. 2020. Differentially private online task assignment in spatial crowdsourcing: A tree-based approach. In Proceedings of the IEEE 36th International Conference on Data Engineering (ICDE\u201920). IEEE, 517\u2013528."},{"key":"e_1_3_1_34_2","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2022.3153451"},{"key":"e_1_3_1_35_2","first-page":"1934","volume-title":"Proceedings of the IEEE\/CIC International Conference on Communications in China (ICCC\u201924)","author":"Wang Jiajun","year":"2024","unstructured":"Jiajun Wang, Xingjian Ding, Jianxiong Guo, Zhiqing Tang, and Deying Li. 2024. Online worker scheduling for maximizing long-term utility in spatiotemporal crowdsensing. In Proceedings of the IEEE\/CIC International Conference on Communications in China (ICCC\u201924). IEEE, 1934\u20131939."},{"key":"e_1_3_1_36_2","article-title":"Malicious participants and fake task detection incorporating gaussian bias","author":"Wang Jian","year":"2024","unstructured":"Jian Wang, Delei Zhao, and Guosheng Zhao. 2024. Malicious participants and fake task detection incorporating gaussian bias. ACM Trans. Internet Technol. 24, 4 (2024), 19:1\u201319:19.","journal-title":"ACM Trans. Internet Technol."},{"key":"e_1_3_1_37_2","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2021.3090764"},{"key":"e_1_3_1_38_2","article-title":"When crowdsensing meets smart cities: A comprehensive survey and new perspectives","author":"Wang Zhenning","year":"2024","unstructured":"Zhenning Wang, Yue Cao, Kai Jiang et\u00a0al. 2024. When crowdsensing meets smart cities: A comprehensive survey and new perspectives. IEEE Commun. Surveys Tutor. (2024).","journal-title":"IEEE Commun. Surveys Tutor."},{"key":"e_1_3_1_39_2","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2020.2973990"},{"issue":"3","key":"e_1_3_1_40_2","doi-asserted-by":"crossref","first-page":"586","DOI":"10.1016\/j.dcan.2023.03.009","article-title":"Starlet: Network defense resource allocation with multi-armed bandits for cloud-edge crowd sensing in IoT","volume":"10","author":"Xia Hui","year":"2024","unstructured":"Hui Xia, Ning Huang, Xuecai Feng et\u00a0al. 2024. Starlet: Network defense resource allocation with multi-armed bandits for cloud-edge crowd sensing in IoT. Digital Commun. Netw. 10, 3 (2024), 586\u2013596.","journal-title":"Digital Commun. Netw."},{"key":"e_1_3_1_41_2","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2021.3059346"},{"key":"e_1_3_1_42_2","first-page":"4040","volume-title":"Proceedings of the IEEE International Conference on Big Data (Big Data\u201922)","author":"Xiao Yunyi","year":"2022","unstructured":"Yunyi Xiao, Yu Yamashita, Hiroyoshi Ito et\u00a0al. 2022. Multi-armed bandit approach to qualification task assignment across multi crowdsourcing platforms. In Proceedings of the IEEE International Conference on Big Data (Big Data\u201922). IEEE, 4040\u20134048."},{"key":"e_1_3_1_43_2","doi-asserted-by":"publisher","DOI":"10.1109\/TNSE.2022.3226422"},{"issue":"8","key":"e_1_3_1_44_2","first-page":"4698","article-title":"Incentive mechanism for spatial crowdsourcing with unknown social-aware workers: A three-stage Stackelberg game approach","volume":"22","author":"Xu Yin","year":"2022","unstructured":"Yin Xu, Mingjun Xiao, Jie Wu, Sheng Zhang et\u00a0al. 2022. Incentive mechanism for spatial crowdsourcing with unknown social-aware workers: A three-stage Stackelberg game approach. IEEE Trans. Mobile Comput. 22, 8 (2022), 4698\u20134713.","journal-title":"IEEE Trans. Mobile Comput."},{"key":"e_1_3_1_45_2","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2023.3305034"},{"key":"e_1_3_1_46_2","doi-asserted-by":"publisher","DOI":"10.1109\/TVT.2023.3238172"},{"key":"e_1_3_1_47_2","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2020.2990221"}],"container-title":["ACM Transactions on Internet Technology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3708893","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3708893","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T01:17:54Z","timestamp":1750295874000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3708893"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,2,11]]},"references-count":46,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2025,2,28]]}},"alternative-id":["10.1145\/3708893"],"URL":"https:\/\/doi.org\/10.1145\/3708893","relation":{},"ISSN":["1533-5399","1557-6051"],"issn-type":[{"value":"1533-5399","type":"print"},{"value":"1557-6051","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,2,11]]},"assertion":[{"value":"2024-10-31","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2024-12-03","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-02-11","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}