Abstract
Last decade has witnessed the explosion in the number of smart mobile phones and other smart devices equipped with powerful sensors. Therefore, various crowdsensing applications which recruit people to complete sensing tasks have sprung up. Designing incentive mechanism plays an indispensable role in crowdsensing network. However, most existing works about incentive mechanism base on the assumption that agents will complete the allocated sensing tasks without any problem. However, when we take the failures of agents into consideration, most existing incentive mechanisms become invalid. Considering a more practical scenario, we suppose that there is a crucial sensing task which needs to remain high enough probability of success completion for a certain period of time and each alternative agent has a certain probability to cover a certain period successfully. To ensure the fault tolerance of the crowdsensing system, we propose two novel incentive mechanisms, single slot coverage (SSC) mechanism and continuous coverage (CC) mechanism, for different problem models, respectively. In our mechanisms, agents' probabilities of success, costs of completing task, start time and end time are all private information. Our objective is to minimize the total costs of selected agents, while ensuring the task is fully covered with a high enough probability over a certain period. Our work presents detailed proofs of the computational efficiency, truthfulness and individual rationality. Besides, we implement extensive simulation to evaluate proposed mechanisms, which validates the properties of our mechanisms.