Abstract
Mobile crowdsourcing is an emerging paradigm which utilizes the distributed smartphones to monitor diverse phenomena about human activities and surrounding environment, enabling a large number of mobile crowdsourcing applications. For those applications to collect sufficient data, motivating smartphone users to be interested in mobile crowdsourcing campaign becomes very significant. Most of the incentive mechanisms assume that tasks are static in mobile crowdsourcing systems. Even for those studies that take the uncertain arrival of tasks into consideration, they always ignore the important geographic location information of the tasks. In the paper, we propose a near-optimal online incentive mechanism based on a more realistic scenario in which crowdsourcing tasks and users both arrive dynamically with tempo-spatial constraints. Through adequate simulations and rigorous theoretical analysis, the online mechanism is proved to satisfy the properties of truthfulness, computational efficiency, individual rationality, and achieve high social welfare and low total payment.
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