  Mobile crowdsensing harnesses the sensing power of modern smartphones to
collect and analyze data beyond the scale of what was previously possible. In a
mobile crowdsensing system, it is paramount to incentivize smartphone users to
provide sensing services in a timely and reliable manner. Given sensed
information is often valid for a limited period of time, the capability of
smartphone users to execute sensing tasks largely depends on their mobility,
which is often uncertain. For this reason, in this paper we propose IncentMe, a
framework that solves this fundamental problem by leveraging game-theoretical
reverse auction mechanism design. After demonstrating that the proposed problem
is NP-hard, we derive two mechanisms that are parallelizable and achieve higher
approximation ratio than existing work. IncentMe has been extensively evaluated
on a road traffic monitoring application implemented using mobility traces of
taxi cabs in San Francisco, Rome, and Beijing. Results demonstrate that the
mechanisms in IncentMe outperform prior work by improving the efficiency in
recruiting participants by 30%.
