{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,28]],"date-time":"2025-10-28T03:16:54Z","timestamp":1761621414726,"version":"build-2065373602"},"reference-count":44,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2018,11,15]],"date-time":"2018-11-15T00:00:00Z","timestamp":1542240000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61871062","61771082"],"award-info":[{"award-number":["61871062","61771082"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Program for Innovation Team Building at Institutions of  Higher Education in Chongqing","award":["CXTDX201601020"],"award-info":[{"award-number":["CXTDX201601020"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Mobile crowdsensing (MCS) is a promising sensing paradigm that leverages diverse embedded sensors in massive mobile devices. One of its main challenges is to effectively select participants to perform multiple sensing tasks, so that sufficient and reliable data is collected to implement various MCS services. Participant selection should consider the limited budget, the different tasks locations, and deadlines. This selection becomes even more challenging when the MCS tries to efficiently accomplish tasks under different heat regions and collect high-credibility data. In this paper, we propose a user characteristics aware participant selection (UCPS) mechanism to improve the credibility of task data in the sparse user region acquired by the platform and to reduce the task failure rate. First, we estimate the regional heat according to the number of active users, average residence time of users and history of regional sensing tasks, and then we divide urban space into high-heat and low-heat regions. Second, the user state information and sensing task records are combined to calculate the willingness, reputation and activity of users. Finally, the above four factors are comprehensively considered to reasonably select the task participants for different heat regions. We also propose task queuing strategies and community assistance strategies to ensure task allocation rates and task completion rates. The evaluation results show that our mechanism can significantly improve the overall data quality and complete sensing tasks of low-heat regions in a timely and reliable manner.<\/jats:p>","DOI":"10.3390\/s18113959","type":"journal-article","created":{"date-parts":[[2018,11,15]],"date-time":"2018-11-15T11:32:47Z","timestamp":1542281567000},"page":"3959","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["User Characteristic Aware Participant Selection for Mobile Crowdsensing"],"prefix":"10.3390","volume":"18","author":[{"given":"Dapeng","family":"Wu","sequence":"first","affiliation":[{"name":"School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China"},{"name":"Key Laboratory of Optical Communication and Networks, Chongqing 400065, China"},{"name":"Key Laboratory of Ubiquitous Sensing and Networking, Chongqing 400065, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haopeng","family":"Li","sequence":"additional","affiliation":[{"name":"School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China"},{"name":"Key Laboratory of Optical Communication and Networks, Chongqing 400065, China"},{"name":"Key Laboratory of Ubiquitous Sensing and Networking, Chongqing 400065, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ruyan","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China"},{"name":"Key Laboratory of Optical Communication and Networks, Chongqing 400065, China"},{"name":"Key Laboratory of Ubiquitous Sensing and Networking, Chongqing 400065, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2018,11,15]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1109\/MCOM.2011.6069707","article-title":"Mobile crowdsensing: Current state and future challenges","volume":"49","author":"Ganti","year":"2011","journal-title":"IEEE Commun. Mag."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"96","DOI":"10.1016\/j.sigpro.2015.10.026","article-title":"Distributed compressive sensing in heterogeneous sensor network","volume":"126","author":"Liang","year":"2016","journal-title":"Signal Proc."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"2958","DOI":"10.1109\/JIOT.2017.2768073","article-title":"Dynamic Trust Relationships Aware Data Privacy Protection in Mobile Crowd- Sensing","volume":"5","author":"Wu","year":"2018","journal-title":"IEEE Internet Things J."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1016\/j.pmcj.2018.06.001","article-title":"An efficient method for physical fields mapping through crowdsensing","volume":"48","author":"Dardari","year":"2018","journal-title":"Pervasive Mob. Comput."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Zhao, Y., Li, S., Hu, S., Su, L., Yao, S., Shao, H., Wang, H., and Abdelzaher, T. (2017, January 18\u201320). GreenDrive: A Smartphone-Based Intelligent Speed Adaptation System with Real-Time Traffic Signal Prediction. Proceedings of the 8th International ACM\/IEEE Conference on Cyber-Physical Systems (ICCPS), Pittsburgh, PA, USA.","DOI":"10.1145\/3055004.3055009"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Zheng, Y., Liu, F., and Hsieh, H. (2013, January 11\u201314). U-Air: When Urban Air Quality Inference Meets Big Data. Proceedings of the Sixth international Conference on Knowledge Discovery and Data Mining, Chicago, IL, USA.","DOI":"10.1145\/2487575.2488188"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"369","DOI":"10.1109\/TASE.2017.2761793","article-title":"CrowdGIS: Updating Digital Maps via Mobile Crowdsensing","volume":"15","author":"Peng","year":"2018","journal-title":"IEEE Trans. Autom. Sci. Eng."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1109\/MCOM.2017.1700481","article-title":"When Collaboration Hugs Intelligence: Content Delivery over Ultra-Dense Networks","volume":"55","author":"Zhou","year":"2017","journal-title":"IEEE Commun. Mag."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"3211","DOI":"10.1109\/TPDS.2013.2297922","article-title":"Green Communication in Energy Renewable Wireless Mesh Networks: Routing, Rate Control, and Power Allocation","volume":"25","author":"Luo","year":"2013","journal-title":"IEEE Trans. Parallel Distrib. Syst."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"88","DOI":"10.1109\/MWC.2015.7054723","article-title":"Opportunistic Communications in Interference Alignment Networks with Wireless Power Transfer","volume":"22","author":"Zhao","year":"2015","journal-title":"IEEE Wirel. Commun."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"803","DOI":"10.1016\/j.future.2017.07.028","article-title":"Security-Oriented Opportunistic Data Forwarding in Mobile Social Networks","volume":"87","author":"Wu","year":"2018","journal-title":"Future Gener. Comput. Syst."},{"key":"ref_12","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":"2017","journal-title":"IEEE Trans. Hum.-Mach. Syst."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1435","DOI":"10.1109\/JSYST.2015.2430362","article-title":"Energy-Aware Participant Selection for Smartphone-Enabled Mobile Crowd Sensing","volume":"11","author":"Liu","year":"2017","journal-title":"IEEE Syst. J."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"2420","DOI":"10.1109\/LCOMM.2017.2732403","article-title":"Load Balanced Mobile User Recruitment for Mobile Crowdsensing Systems","volume":"21","author":"An","year":"2017","journal-title":"IEEE Commun. Lett."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"5497","DOI":"10.1109\/TVT.2015.2439300","article-title":"Interference Alignment Based on Antenna Selection with Imperfect Channel State Information in Cognitive Radio Networks","volume":"65","author":"Li","year":"2016","journal-title":"IEEE Trans. Veh. Technol."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Xiao, M., Wu, J., Huang, H., Huang, L., and Hu, C. (2016, January 8\u201311). Deadline-sensitive User Recruitment for mobile crowdsensing with probabilistic collaboration. Proceedings of the 24th International Conference on Network Protocols (ICNP), Singapore.","DOI":"10.1109\/ICNP.2016.7784408"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"7698","DOI":"10.1109\/TVT.2015.2490679","article-title":"Quality-aware sensing coverage in budget-constrained mobile crowdsensing networks","volume":"65","author":"Zhang","year":"2016","journal-title":"IEEE Trans. Veh. Technol."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1395","DOI":"10.1109\/JIOT.2016.2608141","article-title":"Fine-grained multi-task allocation for participatory sensing with a shared budget","volume":"3","author":"Wang","year":"2016","journal-title":"IEEE Internet Things J."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"107","DOI":"10.1109\/TWC.2014.2332335","article-title":"The Ginibre Point Process as a Model for Wireless Networks with Repulsion","volume":"14","author":"Deng","year":"2015","journal-title":"IEEE Trans. Wirel. Commun."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Zabini, F., and Conti, A. (2016, January 10\u201315). Ginibre sampling and signal reconstruction. Proceedings of the 2016 IEEE International Symposium on Information Theory (ISIT), Barcelona, Spain.","DOI":"10.1109\/ISIT.2016.7541422"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1916","DOI":"10.1109\/TCOMM.2016.2550525","article-title":"The Gauss\u2013Poisson Process for Wireless Networks and the Benefits of Cooperation","volume":"64","author":"Guo","year":"2016","journal-title":"IEEE Trans. Commun."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Zabini, F., Pasolini, G., and Conti, A. (2017, January 25\u201330). On random sampling with nodes attraction: The case of Gauss-Poisson process. Proceedings of the 2017 IEEE International Symposium on Information Theory (ISIT), Aachen, Germany.","DOI":"10.1109\/ISIT.2017.8006935"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"307","DOI":"10.1109\/TMC.2017.2714668","article-title":"Data Quality Guided Incentive Mechanism Design for Crowdsensing","volume":"17","author":"Peng","year":"2018","journal-title":"IEEE Trans. Mob. Comput."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"345","DOI":"10.1109\/TSUSC.2017.2702060","article-title":"Sociability-Driven Framework for Data Acquisition in Mobile Crowdsensing Over Fog Computing Platforms for Smart Cities","volume":"2","author":"Fiandrino","year":"2018","journal-title":"IEEE Trans. Sustain. Comput."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"1382","DOI":"10.1109\/ACCESS.2017.2660461","article-title":"Quantifying User Reputation Scores, Data Trustworthiness, and User Incentives in Mobile Crowd-Sensing","volume":"5","author":"Pouryazdan","year":"2017","journal-title":"IEEE Access"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Xiong, J., Ren, J., Chen, L., Yao, Z., Lin, M., Wu, D., and Niu, B. (2018). Enhancing privacy and availability for data clustering in intelligent electrical service of IoT. IEEE Internet Things J.","DOI":"10.1109\/JIOT.2018.2842773"},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Yu, H., Miao, C., Shen, Z., Leung, C., Chen, Y., and Yang, Q. (2015, January 25\u201330). Efficient task sub-delegation for crowdsourcing. Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, Austin, TX, USA.","DOI":"10.1609\/aaai.v29i1.9337"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"358","DOI":"10.1109\/JIOT.2015.2415035","article-title":"A Crowdsourcing Assignment Model Based on Mobile Crowd Sensing in the Internet of Things","volume":"2","author":"An","year":"2015","journal-title":"IEEE Internet Things J."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"1908","DOI":"10.1109\/TMM.2017.2692648","article-title":"Social Attribute Aware Incentive Mechanism for Device-to-Device Video Distribution","volume":"19","author":"Wu","year":"2017","journal-title":"IEEE Trans. Multimed."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Karaliopoulos, M., Telelis, Q., and Koutsopoulos, I. (May, January 26). User recruitment for mobile crowdsensing over opportunistic networks. Proceedings of the 2015 IEEE Conference on Computer Communications, Kowloon, Hong Kong.","DOI":"10.1109\/INFOCOM.2015.7218612"},{"key":"ref_31","unstructured":"Zhou, T., Cai, Z., Xu, M., and Chen, Y. (2016, January 27\u201330). Leveraging Crowd to improve data credibility for mobile crowdsensing. Proceedings of the 2016 IEEE Symposium on Computers and Communication (ISCC), Messina, Italy."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"2536","DOI":"10.1109\/TITS.2017.2750169","article-title":"Crowdsensing-Based Consensus Incident Report for Road Traffic Acquisition","volume":"19","author":"Wang","year":"2018","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1760","DOI":"10.1109\/TVT.2016.2564641","article-title":"Toward Efficient Mechanisms for Mobile Crowdsensing","volume":"66","author":"Zhang","year":"2017","journal-title":"IEEE Trans. Veh. Technol."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1633","DOI":"10.1109\/TPAMI.2016.2605085","article-title":"Social Collaborative Filtering by Trust","volume":"39","author":"Yang","year":"2017","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"1985","DOI":"10.1049\/iet-com.2017.0052","article-title":"Reputation-aware incentive mechanism for participatory sensing","volume":"11","author":"Sun","year":"2017","journal-title":"IET Commun."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Giannotti, F., Nanni, M., Pedreschi, D., Renso, C., and Trasarti, R. (2009, January 29\u201331). Mining Mobility Behavior from Trajectory Data. Proceedings of the 2009 International Conference on Computational Science and Engineering, Vancouver, BC, Canada.","DOI":"10.1109\/CSE.2009.542"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"12199","DOI":"10.1109\/ACCESS.2017.2719706","article-title":"Social Behaviometrics for Personalized Devices in the Internet of Things Era","volume":"5","author":"Anjomshoa","year":"2017","journal-title":"IEEE Access"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"2323","DOI":"10.1109\/JIOT.2017.2749443","article-title":"SRSM-based Adaptive Relay Selection for D2D Communications","volume":"5","author":"Zhang","year":"2018","journal-title":"IEEE Internet Things J."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"2197","DOI":"10.1109\/TMM.2017.2733300","article-title":"Socially Aware Energy-Efficient Mobile Edge Collaboration for Video Distribution","volume":"19","author":"Wu","year":"2017","journal-title":"IEEE Trans. Multimed."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"2234","DOI":"10.1109\/TMC.2015.2485978","article-title":"Incentive Mechanism Design for Heterogeneous Crowdsourcing Using All-Pay Contests","volume":"15","author":"Luo","year":"2016","journal-title":"IEEE Trans. Mob. Comput."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1109\/MCOM.2018.1700876","article-title":"Knowledge-Centric Edge Computing based on Virtualized D2D Communication Systems","volume":"56","author":"Wang","year":"2018","journal-title":"IEEE Commun. Mag."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"647","DOI":"10.1109\/TNET.2014.2379281","article-title":"Budget-Feasible Online Incentive Mechanisms for Crowdsourcing Tasks Truthfully","volume":"24","author":"Zhao","year":"2016","journal-title":"IEEE\/ACM Trans. Netw."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"179","DOI":"10.1016\/j.adhoc.2016.07.003","article-title":"Layered Admission Control Algorithms with QoE in Heterogeneous Network","volume":"58","author":"Zhang","year":"2017","journal-title":"Ad Hoc Netw."},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Xiao, M., Wu, J., Zhang, S., and Yu, J. (2017, January 1\u20134). Secret-sharing-based secure user recruitment protocol for mobile crowdsensing. Proceedings of the 2017 IEEE Conference on Computer Communications, Atlanta, GA, USA.","DOI":"10.1109\/INFOCOM.2017.8057032"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/18\/11\/3959\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T15:29:51Z","timestamp":1760196591000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/18\/11\/3959"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,11,15]]},"references-count":44,"journal-issue":{"issue":"11","published-online":{"date-parts":[[2018,11]]}},"alternative-id":["s18113959"],"URL":"https:\/\/doi.org\/10.3390\/s18113959","relation":{},"ISSN":["1424-8220"],"issn-type":[{"type":"electronic","value":"1424-8220"}],"subject":[],"published":{"date-parts":[[2018,11,15]]}}}