title: Task and Participant Scheduling of Trading Platforms in Vehicular Participatory Sensing Networks.
abstract: The vehicular participatory sensing network (VPSN) is now becoming more and more prevalent, and additionally has shown its great potential in various applications. A general VPSN consists of many tasks from task, publishers, trading platforms and a crowd of participants. Some literature treats publishers and the trading platform as a whole, which is impractical since they are two independent economic entities with respective purposes. For a trading platform in markets, its purpose is to maximize the profit by selecting tasks and recruiting participants who satisfy the requirements of accepted tasks, rather than to improve the quality of each task. This scheduling problem for a trading platform consists of two parts: which tasks should be selected and which participants to be recruited? In this paper, we investigate the scheduling problem in vehicular participatory sensing with the predictable mobility of each vehicle. A genetic-based trading scheduling algorithm (GTSA) is proposed to solve the scheduling problem. Experiments with a realistic dataset of taxi trajectories demonstrate that GTSA algorithm is efficient for trading platforms to gain considerable profit in VPSN.
authors.affiliation: School of Software, Tsinghua University, Beijing 100084, China. shy15@mails.tsinghua.edu.cn.
authors.forename: Heyuan
authors.initials: H
authors.lastname: Shi
authors.affiliation: Department of Electrical & Computer Engineering, Portland State University, P.O. Box 751, Portland, OR 97207-0751, USA. song@ece.pdx.edu.
authors.forename: Xiaoyu
authors.initials: X
authors.lastname: Song
authors.affiliation: School of Software, Tsinghua University, Beijing 100084, China. guming@tsinghua.edu.cn.
authors.forename: Ming
authors.initials: M
authors.lastname: Gu
authors.affiliation: School of Software, Tsinghua University, Beijing 100084, China. sunjg@tsinghua.edu.cn.
authors.forename: Jiaguang
authors.initials: J
authors.lastname: Sun
keywords: participants recruitment; participatory sensing networks; scheduling; tasks selection; vehicular sensor networks