? FIMI:A Constant Frugal Incentive Mechanism for Time Window Coverage in Mobile Crowdsensing
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Journal of Computer Science and Technology 2017, Vol. 32 Issue (5) :919-935    DOI: 10.1007/s11390-017-1773-4
Special Section on Crowdsourced Data Management Current Issue | Archive | Adv Search << Previous Articles | Next Articles >>
FIMI:A Constant Frugal Incentive Mechanism for Time Window Coverage in Mobile Crowdsensing
Jia Xu1,2, Member, CCF, ACM, IEEE, Jian-Ren Fu1, De-Jun Yang3, Member, IEEE, Li-Jie Xu1,2, Lei Wang1,2, Tao Li1,2, Member, IEEE
1 School of Computer Science, Nanjing University of Posts and Telecommunications, Nanjing 210023, China;
2 Jiangsu Key Laboratory of Big Data Security and Intelligent Processing, Nanjing University of Posts and Telecommunications, Nanjing 210023, China;
3 Department of Computer Science, Colorado School of Mines, Golden 80401, U.S.A

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Abstract Mobile crowdsensing has become an efficient paradigm for performing large scale sensing tasks. An incentive mechanism is important for a mobile crowdsensing system to stimulate participants and to achieve good service quality. In this paper, we explore truthful incentive mechanisms that focus on minimizing the total payment for a novel scenario, where the platform needs the complete sensing data in a Requested Time Window (RTW). We model this scenario as a reverse auction and design FIMI, a constant Frugal Incentive Mechanism for tIme window coverage. FIMI consists of two phases, the candidate selection phase and the winner selection phase. In the candidate selection phase, it selects two most competitive disjoint feasible user sets. Afterwards, in the winner selection phase, it finds all the interchangeable user sets through a graph-theoretic approach. For every pair of such user sets, FIMI chooses one of them by the weighted cost. Further, we extend FIMI to the scenario, where the RTW needs to be covered more than once. Through both rigorous theoretical analysis and extensive simulations, we demonstrate that the proposed mechanisms achieve the properties of RTW feasibility (or RTW multi-coverage) computation efficiency, individual rationality, truthfulness, and constant frugality.
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Keywordscrowdsensing   incentive mechanism   constant frugality     
Received 2017-02-17;
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The work was supported by the National Natural Science Foundation of China under Grant Nos. 61472193 and 61472192, the Young Scientists Fund of the National Natural Science Foundation of China under Grant No. 61502251, the Major Research Plan of the National Natural Science Foundation of China under Grant No. 91646116, the Natural Science Foundation of USA under Grant Nos. 1444059, 1420881 and 1717315, and the Natural Science Foundation of Jiangsu Province of China under Grant Nos. BK20141429, BK20151511 and BE2016776.

About author: Jia Xu received his M.S.degree in computer science from Yangzhou University,Yangzhou,in 2006,and his Ph.D.degree in computer science from Nanjing University of Science and Technology,Nanjing,in 2010.He is currently a professor at Nanjing University of Posts and Telecommunications, Nanjing.
Cite this article:   
Jia Xu, Jian-Ren Fu, De-Jun Yang, Li-Jie Xu, Lei Wang, Tao Li.FIMI:A Constant Frugal Incentive Mechanism for Time Window Coverage in Mobile Crowdsensing[J]  Journal of Computer Science and Technology, 2017,V32(5): 919-935
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http://jcst.ict.ac.cn:8080/jcst/EN/10.1007/s11390-017-1773-4
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