LAUSR

Mobile crowdsensing systems aim at providing various novel sensing applications by recruiting pervasive users with mobile devices, which are now equipped with enriched built-in sensors (e.g., GPS, microphone, camera, gyroscope, accelerometer, etc.). A key factor to enable such systems is substantial participation of large amount of mobile users. In this paper, we focus on the data collection in mobile opportunistic crowdsensing, where the data can be transferred between mobile users via opportunistic device-to-device communications. The goal is to deliver the sensed data from the collector to the corresponding requester, which can maximize the collector’s rewards. Here, we assume that the data collection has time-sensitive characteristics, i.e., the reward is time-sensitive. We consider selfish mobile users with rational behaviors, and propose a credit-based incentive-aware mechanism to stimulate mobile users to participate in data collection for mobile opportunistic crowdsensing. Particularly, we propose an effective mechanism to define the expected rewards for the sensed data, and formulate the sensed data trading as a two-person cooperative game, whose solution is obtained through the Nash bargaining theory. Extensive simulations based on both synthetic and real-world mobility traces are conducted to validate the efficiency of our incentive-aware mechanisms.