Deadline-Sensitive User Recruitment for Probabilistically Collaborative Mobile Crowdsensing

Mobile crowdsensing is a new paradigm in which a group of mobile users exploit their carried smart devices to cooperatively perform a large-scale sensing job over urban environments. In this paper, we focus on the Deadline-sensitive User Recruitment (DUR) problem for probabilistically collaborative mobile crowdsensing, in which mobile users perform sensing tasks with certain probabilities, and multiple users might be recruited to cooperatively perform a common task, ensuring that the expected completion time be no larger than a deadline. In order to solve this problem, we propose a greedy approximation algorithm, which can achieve the logarithmic approximation ratio.