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Mobile sensing has become a promising paradigm for mobile users to obtaininformation by task crowdsourcing. However, due to the social preferences ofmobile users, the quality of sensing reports may be impacted by the underlyingsocial attributes and selfishness of individuals. Therefore, it is crucial toconsider the social impacts and trustworthiness of mobile users when selectingtask participants in mobile sensing. In this paper, we propose a Social AwareCrowdsourcing with Reputation Management (SACRM) scheme to select thewell-suited participants and allocate the task rewards in mobile sensing.Specifically, we consider the social attributes, task delay and reputation incrowdsourcing and propose a participant selection scheme to choose thewell-suited participants for the sensing task under a fixed task budget. Areport assessment and rewarding scheme is also introduced to measure thequality of the sensing reports and allocate the task rewards based the assessedreport quality. In addition, we develop a reputation management scheme toevaluate the trustworthiness and cost performance ratio of mobile users forparticipant selection. Theoretical analysis and extensive simulationsdemonstrate that SACRM can efficiently improve the crowdsourcing utility andeffectively stimulate the participants to improve the quality of their sensingreports.

SACRM: Social Aware Crowdsourcing with Reputation Management in Mobile Sensing