? 移动群智感知中一种时间窗口覆盖的常节俭度激励机制
Journal of Computer Science and Technology
Quick Search in JCST
 Advanced Search 
      Home | PrePrint | SiteMap | Contact Us | Help
 
Indexed by   SCIE, EI ...
Bimonthly    Since 1986
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 << Previous Articles | Next Articles >>
移动群智感知中一种时间窗口覆盖的常节俭度激励机制
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
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

摘要
参考文献
相关文章
Download: [PDF 1001KB]  
摘要 移动群智感知已经成为执行大规模感知任务的新型模式。在群智感知中,激励机制对于刺激用户参与群智感知和提供服务质量十分重要。本文致力于设计一种真实的激励机制以最小化总支付。本文考虑群智感知平台需要收集能覆盖一个请求时间窗口的感知数据。我们将这个问题建模成一个反向拍卖过程,并提出了一个常节俭性的激励机制FIMI。FIMI分为候选者选择和赢家选择两个阶段。在候选者选择中,选择两个最具有竞争力的不相交的可行的用户集。然后在赢家选择中通过图理论方法寻找可替代用户集。对每组可替代用户集,FIMI选择其中带权成本最小的用户集作为赢家。进一步地,本文将FIMI扩展到请求时间窗口需要被多次覆盖的情形。严格的理论分析和大量仿真表明,所提出的激励机制具有请求时间窗口可行性,计算有效性,个人理性,真实性和常节俭性。
关键词群智感知   激励机制   常节俭度     
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.
Keywordscrowdsensing   incentive mechanism   constant frugality     
Received 2017-02-17;
本文基金:

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.
引用本文:   
Jia Xu, Jian-Ren Fu, De-Jun Yang, Li-Jie Xu, Lei Wang, Tao Li.移动群智感知中一种时间窗口覆盖的常节俭度激励机制[J]  Journal of Computer Science and Technology , 2017,V32(5): 919-935
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
链接本文:  
http://jcst.ict.ac.cn:8080/jcst/CN/10.1007/s11390-017-1773-4
Copyright 2010 by Journal of Computer Science and Technology