{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,22]],"date-time":"2025-10-22T10:40:30Z","timestamp":1761129630280,"version":"build-2065373602"},"reference-count":47,"publisher":"MDPI AG","issue":"14","license":[{"start":{"date-parts":[[2019,7,18]],"date-time":"2019-07-18T00:00:00Z","timestamp":1563408000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Nature Science Foundation of China","award":["91646202"],"award-info":[{"award-number":["91646202"]}]},{"name":"National Key R&amp;D Program of China","award":["2018YFB1404400, 2018YFB1402700"],"award-info":[{"award-number":["2018YFB1404400, 2018YFB1402700"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>With the rapid development of mobile networks and smart terminals, mobile crowdsourcing has aroused the interest of relevant scholars and industries. In this paper, we propose a new solution to the problem of user selection in mobile crowdsourcing system. The existing user selection schemes mainly include: (1) find a subset of users to maximize crowdsourcing quality under a given budget constraint; (2) find a subset of users to minimize cost while meeting minimum crowdsourcing quality requirement. However, these solutions have deficiencies in selecting users to maximize the quality of service of the task and minimize costs. Inspired by the marginalism principle in economics, we wish to select a new user only when the marginal gain of the newly joined user is higher than the cost of payment and the marginal cost associated with integration. We modeled the scheme as a marginalism problem of mobile crowdsourcing user selection (MCUS-marginalism). We rigorously prove the MCUS-marginalism problem to be NP-hard, and propose a greedy random adaptive procedure with annealing randomness (GRASP-AR) to achieve maximize the gain and minimize the cost of the task. The effectiveness and efficiency of our proposed approaches are clearly verified by a large scale of experimental evaluations on both real-world and synthetic data sets.<\/jats:p>","DOI":"10.3390\/s19143158","type":"journal-article","created":{"date-parts":[[2019,7,18]],"date-time":"2019-07-18T03:11:42Z","timestamp":1563419502000},"page":"3158","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Using Greedy Random Adaptive Procedure to Solve the User Selection Problem in Mobile Crowdsourcing"],"prefix":"10.3390","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3518-7851","authenticated-orcid":false,"given":"Jian","family":"Yang","sequence":"first","affiliation":[{"name":"School of Computer and Communication Engineering, Beijing Key Laboratory of Knowledge Engineering for Materials Science, University of Science and Technology Beijing, Beijing 100083, China"}]},{"given":"Xiaojuan","family":"Ban","sequence":"additional","affiliation":[{"name":"School of Computer and Communication Engineering, Beijing Key Laboratory of Knowledge Engineering for Materials Science, University of Science and Technology Beijing, Beijing 100083, China"}]},{"given":"Chunxiao","family":"Xing","sequence":"additional","affiliation":[{"name":"Research Institute of Information, Beijing National Research Center for Information Science and Technology, Department of Computer Science and Technology, Institute of Internet Industry, Tsinghua University, Beijing 100084, China"}]}],"member":"1968","published-online":{"date-parts":[[2019,7,18]]},"reference":[{"key":"ref_1","first-page":"31","article-title":"Mobile Crowd Sensing Survey","volume":"48","author":"Guo","year":"2015","journal-title":"ACM Comput. Surv."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Boubiche, D.E., Imran, M., Maqsood, A., and Shoaib, M. (2018). Mobile Crowd Sensing\u2014Taxonomy, Applications, Challenges, and Solutions. Comput. Hum. Behav.","DOI":"10.1016\/j.chb.2018.10.028"},{"key":"ref_3","unstructured":"(2019, June 05). Global Mobile Markets Report. Available online: https:\/\/newzoo.com\/insights\/trend-reports\/newzoo-global-mobile-market-report-2018-light-version\/."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Amaxilatis, D., Mylonas, G., Diez, L., Theodoridis, E., Guti\u00e9rrez, V., and Mu\u00f1oz, L. (2018). Managing Pervasive Sensing Campaigns via an Experimentation-as-a-Service Platform for Smart Cities. Sensors, 18.","DOI":"10.3390\/s18072125"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Choque, J., Diez, L., Medela, A., and Mu\u00f1oz, L. (2019). Experimentation Management in the Co-Created Smart-City: Incentivization and Citizen Engagement. Sensors, 19.","DOI":"10.3390\/s19020411"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Khan, S.Z., Rahuman, W.M.A., Dey, S., Anwar, T., and Kayes, A.S.M. (2017, January 16\u201317). RoadCrowd: An Approach to Road Traffic Forecasting at Junctions Using Crowd-Sourcing and Bayesian Model. Proceedings of the 2017 International Conference on Research and Innovation in Information Systems (ICRIIS), Langkawi, Malaysia.","DOI":"10.1109\/ICRIIS.2017.8002451"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"18665","DOI":"10.1109\/ACCESS.2017.2754269","article-title":"Localized Confident Information Coverage Hole Detection in Internet of Things for Radioactive Pollution Monitoring","volume":"5","author":"Yi","year":"2017","journal-title":"IEEE Access"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"2390","DOI":"10.1109\/TKDE.2012.153","article-title":"T-Finder: A Recommender System for Finding Passengers and Vacant Taxis","volume":"25","author":"Yuan","year":"2013","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Abu-Elkheir, M., Hassanein, H.S., and Oteafy, S.M.A. (2016, January 5\u20139). Enhancing Emergency Response Systems through Leveraging Crowdsensing and Heterogeneous Data. Proceedings of the 2016 International Wireless Communications and Mobile Computing Conference (IWCMC), Paphos, Cyprus.","DOI":"10.1109\/IWCMC.2016.7577055"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"56","DOI":"10.1016\/j.dss.2016.06.019","article-title":"Balancing Quality and Budget Considerations in Mobile Crowdsourcing","volume":"90","author":"Miao","year":"2016","journal-title":"Decis. Support Syst."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1016\/j.jnca.2019.01.008","article-title":"Multi-Worker Multi-Task Selection Framework in Mobile Crowd Sourcing","volume":"130","author":"Abououf","year":"2019","journal-title":"J. Netw. Comput. Appl."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1637","DOI":"10.1109\/TMC.2017.2771259","article-title":"Multi-Objective Optimization Based Allocation of Heterogeneous Spatial Crowdsourcing Tasks","volume":"17","author":"Wang","year":"2018","journal-title":"IEEE Trans. Mob. Comput."},{"key":"ref_13","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_14","doi-asserted-by":"crossref","first-page":"18613","DOI":"10.3390\/s150818613","article-title":"Scalable and Cost-Effective Assignment of Mobile Crowdsensing Tasks Based on Profiling Trends and Prediction: The ParticipAct Living Lab Experience","volume":"15","author":"Bellavista","year":"2015","journal-title":"Sensors"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"123","DOI":"10.1016\/j.pmcj.2017.06.010","article-title":"Trajectory Segment Selection with Limited Budget in Mobile Crowd Sensing","volume":"40","author":"Chen","year":"2017","journal-title":"Pervasive Mob. Comput."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"134","DOI":"10.1016\/j.jpdc.2017.09.014","article-title":"QoS Prediction for Service Recommendations in Mobile Edge Computing","volume":"127","author":"Wang","year":"2017","journal-title":"J. Parallel Distrib. Comput."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"370","DOI":"10.1109\/JIOT.2015.2409151","article-title":"A Survey of Incentive Techniques for Mobile Crowd Sensing","volume":"2","author":"Jaimes","year":"2015","journal-title":"IEEE Internet Things J."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Jin, H., Su, L., Chen, D., Nahrstedt, K., and Xu, J. (2015, January 22\u201325). Quality of Information Aware Incentive Mechanisms for Mobile Crowd Sensing Systems. Proceedings of the 16th ACM International Symposium on Mobile Ad Hoc Networking and Computing, MobiHoc\u20192015, Hangzhou, China.","DOI":"10.1145\/2746285.2746310"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"2019","DOI":"10.1109\/TNET.2018.2840098","article-title":"Incentive Mechanism for Privacy-Aware Data Aggregation in Mobile Crowd Sensing Systems","volume":"26","author":"Jin","year":"2018","journal-title":"IEEE\/ACM Trans. Netw."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"6940","DOI":"10.1109\/TWC.2017.2734758","article-title":"Incentivizing Crowdsensing With Location-Privacy Preserving","volume":"16","author":"Wang","year":"2017","journal-title":"IEEE Trans. Wirel. Commun."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1851","DOI":"10.1109\/TMC.2017.2780091","article-title":"Frameworks for Privacy-Preserving Mobile Crowdsensing Incentive Mechanisms","volume":"17","author":"Lin","year":"2017","journal-title":"IEEE Trans. Mob. Comput."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"100","DOI":"10.1016\/j.comnet.2016.11.020","article-title":"Towards Energy-Efficient Task Scheduling on Smartphones in Mobile Crowd Sensing Systems","volume":"115","author":"Wang","year":"2017","journal-title":"Comput. Netw."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Zhao, Y., Li, Y., Wang, Y., Su, H., and Zheng, K. (2017, January 6\u201310). Destination-Aware Task Assignment in Spatial Crowdsourcing. Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, CIKM\u201917, Singapore.","DOI":"10.1145\/3132847.3132894"},{"key":"ref_24","first-page":"2","article-title":"A Server-Assigned Spatial Crowdsourcing Framework","volume":"1","author":"To","year":"2016","journal-title":"ACM Trans. Spat. Algorithms Syst."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"107","DOI":"10.1016\/j.dss.2018.03.010","article-title":"Toward a Real-Time and Budget-Aware Task Package Allocation in Spatial Crowdsourcing","volume":"110","author":"Wu","year":"2018","journal-title":"Decis. Support Syst."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"36","DOI":"10.1016\/j.eswa.2016.03.022","article-title":"Efficient Task Assignment for Spatial Crowdsourcing: A Combinatorial Fractional Optimization Approach with Semi-Bandit Learning","volume":"58","author":"Curry","year":"2016","journal-title":"Expert Syst. Appl."},{"key":"ref_27","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_28","doi-asserted-by":"crossref","first-page":"210","DOI":"10.1016\/j.ins.2019.03.071","article-title":"User Selection Utilizing Data Properties in Mobile Crowdsensing","volume":"490","author":"Wang","year":"2019","journal-title":"Inf. Sci."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"He, Z., Cao, J., and Liu, X. (May, January 26). High Quality Participant Recruitment in Vehicle-Based Crowdsourcing Using Predictable Mobility. Proceedings of the 2015 IEEE Conference on Computer Communications (INFOCOM), Hong Kong, China.","DOI":"10.1109\/INFOCOM.2015.7218644"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"243","DOI":"10.1002\/bdm.375","article-title":"Intuitions about declining marginal utility","volume":"255","author":"Greene","year":"2001","journal-title":"J. Behav. Decis. Mak."},{"key":"ref_31","unstructured":"(2019, May 13). Marginalism Principle. Available online: http:\/\/www.opentextbooks.org.hk\/system\/files\/export\/15\/15497\/pdf\/Principles_of_Managerial_Economics_15497.pdf."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"219","DOI":"10.1016\/j.bushor.2011.01.003","article-title":"The New WTP: Willingness to Participate","volume":"54","author":"Parent","year":"2011","journal-title":"Bus. Horiz."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"473","DOI":"10.1016\/j.procs.2019.01.275","article-title":"An Attack-Resistant Reputation Management System For Mobile Ad Hoc Networks","volume":"147","author":"Zhang","year":"2019","journal-title":"Procedia Comput. Sci."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"581","DOI":"10.1007\/s10115-014-0780-9","article-title":"A Topic-Biased User Reputation Model in Rating Systems","volume":"44","author":"Li","year":"2015","journal-title":"Knowl. Inf. Syst."},{"key":"ref_35","unstructured":"Josang, A., and Ismail, R. (2002, January 17\u201319). The Beta Reputation System. Proceedings of the 15th Bled Electronic Commerce Conference, Bled, Slovenia."},{"key":"ref_36","unstructured":"(2019, May 05). Euclidean Distance. Available online: https:\/\/www.pbarrett.net\/techpapers\/euclid.pdf."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"37","DOI":"10.14778\/2535568.2448938","article-title":"Less is More: Selecting Sources Wisely for Integration","volume":"6","author":"Dong","year":"2012","journal-title":"Proc. VLDB Endow."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Yang, J., and Xing, C. (2019). Data Source Selection Based on an Improved Greedy Genetic Algorithm. Symmetry, 11.","DOI":"10.3390\/sym11020273"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"1176","DOI":"10.1016\/j.cor.2012.11.023","article-title":"An Effective GRASP and Tabu Search for the 0-1 Quadratic Knapsack Problem","volume":"40","author":"Yang","year":"2013","journal-title":"Comput. Oper. Res."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"167","DOI":"10.1016\/j.comnet.2018.09.011","article-title":"Greedy Randomized Adaptive Search Procedure for Joint Optimization of Unicast and Anycast Traffic in Spectrally-Spatially Flexible Optical Networks","volume":"146","author":"Lechowicz","year":"2018","journal-title":"Comput. Netw."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1109\/101.17235","article-title":"Simulated Annealing Algorithms: An Overview","volume":"5","author":"Rutenbar","year":"1989","journal-title":"IEEE Circuits Devices Mag."},{"key":"ref_42","unstructured":"(2019, May 05). The Real-World Data. Available online: http:\/\/www.mcm.edu.cn\/html_cn\/node\/460baf68ab0ed0e1e557a0c79b1c4648.html."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"333","DOI":"10.1016\/j.pmcj.2017.01.005","article-title":"A QoS-Sensitive Task Assignment Algorithm for Mobile Crowdsensing","volume":"41","author":"Hu","year":"2017","journal-title":"Pervasive Mob. Comput."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"1022","DOI":"10.14778\/2794367.2794372","article-title":"Reliable Diversity-Based Spatial Crowdsourcing by Moving Workers","volume":"8","author":"Cheng","year":"2015","journal-title":"Proc. VLDB Endow."},{"key":"ref_45","first-page":"411","article-title":"A New Hybrid Particle Swarm Optimization and Greedy for 0\u20131 Knapsack Problem","volume":"1","author":"Nguyen","year":"2016","journal-title":"Indones. J. Electr. Eng. Comput. Sci."},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Yang, J., Zhao, C., and Xing, C. (2019). Big Data Market Optimization Pricing Model Based on Data Quality. Complexity, 2019.","DOI":"10.1155\/2019\/5964068"},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Yang, J., and Xing, C. (2019). Personal Data Market Optimization Pricing Model Based on Privacy Level. Information, 10.","DOI":"10.1155\/2019\/5964068"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/19\/14\/3158\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T13:06:54Z","timestamp":1760188014000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/19\/14\/3158"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,7,18]]},"references-count":47,"journal-issue":{"issue":"14","published-online":{"date-parts":[[2019,7]]}},"alternative-id":["s19143158"],"URL":"https:\/\/doi.org\/10.3390\/s19143158","relation":{},"ISSN":["1424-8220"],"issn-type":[{"type":"electronic","value":"1424-8220"}],"subject":[],"published":{"date-parts":[[2019,7,18]]}}}