Online budget-limited pricing incentives for remote mobile sensing

Mobile crowdsensing (MCS) receives extensive interest due to enabling many novel applications at lower cost. However in pricing incentive scenes of MCS, utility from mobile users presents complex distributions due to mobility, changes of abilities and resource consumption such as device’s energy and memory, especially for submodular MCS with more general distributions. However, existing works only focus on homogeneous and heterogeneous MCS, whether multi-request pricing scene or single-request pricing scene. To the end, in this paper, we investigate online pricing issues for submodular MCS. Moreover, we apply a multiple-stage budget-limited process and robust mean estimators to design budget-limited pricing incentive for submodular MCS. Extensive simulations demonstrate that our mechanisms outweigh existing benchmarks.