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Monetary incentives in participatory sensing using multi-attributive auctions

Published: 01 August 2012 Publication History

Abstract

Participation of people is the most important factor in providing high quality of service in participatory sensing applications. In this paper, we study monetary incentives in order to stimulate user's participation, especially in applications that rely on real-time data. Providing such incentives is hard because the service provider cannot determine the price at which each user would be willing to sell his own sensing data. Introducing traditional reverse auction mechanisms would allow to reveal this value, but they do not take under consideration the fact that sensing data are not all of same quality. This paper applies multi-attributive auction mechanisms that besides negotiation on the price, help service providers select the sensing data of the highest quality and also give users the incentive to further improve on them. We verify the benefits of this scheme using simulation experiments and we identify further research challenges.

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  • (2024)Auction-Based Crowdsourced First and Last Mile LogisticsIEEE Transactions on Mobile Computing10.1109/TMC.2022.321988123:1(180-193)Online publication date: 1-Jan-2024
  • (2022)A reputation-based and privacy-preserving incentive scheme for mobile crowd sensing: a deep reinforcement learning approachWireless Networks10.1007/s11276-022-03111-930:6(4685-4698)Online publication date: 5-Sep-2022
  • (2021)Key Research Issues and Related Technologies in Crowdsourcing Data CollectionWireless Communications & Mobile Computing10.1155/2021/87458972021Online publication date: 1-Jan-2021
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Published In

cover image International Journal of Parallel, Emergent and Distributed Systems
International Journal of Parallel, Emergent and Distributed Systems  Volume 27, Issue 4
August 2012
92 pages
ISSN:1744-5760
EISSN:1744-5779
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Taylor & Francis, Inc.

United States

Publication History

Published: 01 August 2012

Author Tags

  1. monetary incentives
  2. multi-attributive actions
  3. participatory sensing
  4. privacy
  5. sensing data

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Cited By

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  • (2024)Auction-Based Crowdsourced First and Last Mile LogisticsIEEE Transactions on Mobile Computing10.1109/TMC.2022.321988123:1(180-193)Online publication date: 1-Jan-2024
  • (2022)A reputation-based and privacy-preserving incentive scheme for mobile crowd sensing: a deep reinforcement learning approachWireless Networks10.1007/s11276-022-03111-930:6(4685-4698)Online publication date: 5-Sep-2022
  • (2021)Key Research Issues and Related Technologies in Crowdsourcing Data CollectionWireless Communications & Mobile Computing10.1155/2021/87458972021Online publication date: 1-Jan-2021
  • (2020)Towards Demand-Driven Dynamic Incentive for Mobile Crowdsensing SystemsIEEE Transactions on Wireless Communications10.1109/TWC.2020.298827119:7(4907-4918)Online publication date: 9-Jul-2020
  • (2020)Revenue maximization of Internet of things provider using variable neighbourhood searchJournal of Global Optimization10.1007/s10898-020-00894-z78:2(375-396)Online publication date: 1-Oct-2020
  • (2019)Incentive-Based Crowdsourcing of Hotspot ServicesACM Transactions on Internet Technology10.1145/322904719:1(1-24)Online publication date: 29-Jan-2019
  • (2018)Truthful incentive mechanism with location privacy-preserving for mobile crowdsourcing systemsComputer Networks: The International Journal of Computer and Telecommunications Networking10.1016/j.comnet.2018.02.008135:C(32-43)Online publication date: 22-Apr-2018
  • (2016)Adopting incentive mechanisms for large-scale participation in mobile crowdsensingHuman-centric Computing and Information Sciences10.1186/s13673-016-0080-36:1(1-31)Online publication date: 1-Dec-2016
  • (2016)Designing Secure and Dependable Mobile Sensing Mechanisms With Revenue GuaranteesIEEE Transactions on Information Forensics and Security10.1109/TIFS.2015.247873911:1(100-113)Online publication date: 1-Jan-2016
  • (2016)Incentives for Mobile Crowd Sensing: A SurveyIEEE Communications Surveys & Tutorials10.1109/COMST.2015.241552818:1(54-67)Online publication date: 27-Jan-2016
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