A Cross-Space, Multi-interaction-Based Dynamic Incentive Mechanism for Mobile Crowd Sensing

With the surge of varied crowd sensing systems, active user participation becomes a crucial factor that determines whether a crowd sensing system can provide good service quality. To encourage user participation in mobile crowd sensing, we propose a novel incentive mechanism called CSII -- a Cross-Space, multi-Interaction-based Incentive mechanism. CSII can estimate the value of a task based on the sensing context and historical data. It then has multiple interactions with both the task requester and the candidate contributors to provide a suggestion on budget and select suitable people to form the worker group. Finally, the requester pays the workers´ reward that they deserved by reverse auction based on their reputation and bids. Both online and offline data are leveraged to estimate task value and user quality for a particular task. Experiments show that the incentive mechanism can achieve good performance in terms of acceptance ratio, overpayment ratio, user utility, and so on.