Mobile Crowd Sensing (MCS) is a new paradigm which takes advantage of pervasive mobile devices to efficiently collect data, enabling numerous novel applications. To achieve good service quality for an MCS application, incentive mechanisms are necessary to attract more user participation. Most of existing mechanisms apply only for the offline scenario where all users report their strategic types in advance. On the contrary, we focus on a more realistic scenario where users arrive one by one

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... e in a random order. Based on the online auction model, we investigate the problem that users submit their private types to the crowdsourcer when arrive, and the crowdsourcer aims at selecting a subset of users before a specified deadline for maximizing the value of services (assumed to be a non-negative monotone submodular function) provided by selected users under a budget constraint. We design two online mechanisms, OMZ and OMG, satisfying the computational efficiency, individual rationality, budget feasibility, truthfulness, consumer sovereignty and constant competitiveness under the zero arrival-departure interval case and a more general case, respectively. Through extensive simulations, we evaluate the performance and validate the theoretical properties of our online mechanisms. Index Terms-Crowdsourcing, incentive mechanism design, online auction. * If the user fails to complete the tasks, or fails to meet the time or quality requirement, the crowdsourcer can give no payment or less payment, or records his/her reputation for assisting in future decision [20] .