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The acquirement of large amounts of sensing data is a fundamental issue in IoT. An efficient way is obtaining sufficient data by the mobile crowdsensing. It is a promising paradigm which leverages the sensing capacity of portable mobile devices. The crowdsensing platform is the key entity who allocates tasks to participants in a mobile crowdsensing system. The strategy of task allocating is crucial for the crowdsensing platform, since it affects the data requester\u2019s confidence, the participant\u2019s confidence, and its own benefit. Traditional allocating algorithms regard the privacy preservation, which may lose the confidence of participants. In this paper, we propose a novel three-step algorithm which allocates tasks to participants with privacy consideration. It maximizes the benefit of the crowdsensing platform and meanwhile preserves the privacy of participants. Evaluation results on both benefit and privacy aspects show the effectiveness of our proposed algorithm.<\/jats:p>","DOI":"10.1155\/2019\/3154917","type":"journal-article","created":{"date-parts":[[2019,4,1]],"date-time":"2019-04-01T19:33:04Z","timestamp":1554147184000},"page":"1-13","source":"Crossref","is-referenced-by-count":3,"title":["A Novel Task Allocation Algorithm in Mobile Crowdsensing with Spatial Privacy Preservation"],"prefix":"10.1155","volume":"2019","author":[{"given":"Wenyi","family":"Tang","sequence":"first","affiliation":[{"name":"The School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qi","family":"Jin","sequence":"additional","affiliation":[{"name":"The School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China"},{"name":"Chengdu Municipal Public Security Bureau, 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