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Sensors 2016, 16(12), 2013; doi:10.3390/s16122013

Task and Participant Scheduling of Trading Platforms in Vehicular Participatory Sensing Networks

1
School of Software, Tsinghua University, Beijing 100084, China
2
Department of Electrical & Computer Engineering, Portland State University, P.O. Box 751, Portland, OR 97207-0751, USA
*
Author to whom correspondence should be addressed.
Academic Editors: Mianxiong Dong, Zhi Liu, Anfeng Liu and Didier El Baz
Received: 30 October 2016 / Revised: 23 November 2016 / Accepted: 23 November 2016 / Published: 28 November 2016
(This article belongs to the Special Issue New Paradigms in Cyber-Physical Social Sensing)
View Full-Text   |   Download PDF [1323 KB, uploaded 30 November 2016]   |  

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. View Full-Text
Keywords: participatory sensing networks; vehicular sensor networks; tasks selection; participants recruitment; scheduling participatory sensing networks; vehicular sensor networks; tasks selection; participants recruitment; scheduling
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Shi, H.; Song, X.; Gu, M.; Sun, J. Task and Participant Scheduling of Trading Platforms in Vehicular Participatory Sensing Networks. Sensors 2016, 16, 2013.

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