Quality-Assure and Budget-Aware Task Assignment for Spatial Crowdsourcing

With the increasingly ubiquity of mobile devices and the rapid development of communication technologies, spatial crowdsourcing has become a hot topic research among academic and industry community. As participants may possess different capabilities and reliabilities, as well as the changeable locations and available time slots of both tasks and potential workers, a major challenge is how to assign spatial tasks to appropriate workers from lots of potential applicants, which should assure the result quality of the crowdsourcing task. Also, as different workers may receive variable rewards for the same task, the crowdsourcing budget renders task assignment more complicated. This paper focuses on the issue of quality assurance for task assignment in spatial crowdsourcing while considering budget limitation. The problem is first modeled as Quality-assure and Budget-aware Task Assignment (QBTA) problem. Then two two-phase greedy algorithms are proposed. Finally, experiments are conducted to show the effectiveness and efficiency of the algorithms.