Multi-Dimensional Incentive Mechanism in Mobile Crowdsourcing with Moral Hazard - 2018


In current wireless Communication systems, there is a rapid development of location based mostly services, that will play an important role in the future 5G networks. One key feature in providing the service is that the mobile crowdsourcing in which a central cloud node denoted because the principal collects location primarily based data from a giant cluster of users. In this Project, we have a tendency to investigate the matter of how to supply continuous incentives based on user's performances to encourage users' participation in the crowdsourcing, which can be spoken the moral hazard downside within the contract theory. We have a tendency to not only propose the one-dimensional performance-reward connected contract, but conjointly extend this basic model into the multi-dimensional contract. First, an incentive contract which rewards users by evaluating their performances from multiple dimensions is proposed. Then, the utility maximization problem of the principal in both one-dimension and multi-dimension are formulated. Furthermore, we detailed the analysis of the multi-dimensional contract to allocate incentives. Finally, we use the numerical results to analyze the optimal reward package, and compare the principal's utility underneath the different incentive mechanisms. Results demonstrate that by using the proposed incentive mechanism, the principal successfully maximizes the utilities, and the users obtain continuous incentives to participate in the crowdsourcing activity.

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