An integrated incentive framework for mobile Crowdsourced sensing

Wei Dai, Yufeng Wang, Qun Jin, Jianhua Ma

Research output: Contribution to journalArticle

18 Citations (Scopus)

Abstract

Currently, mobile devices (e.g., smartphones) are equipped with multiple wireless interfaces and rich builtin functional sensors that possess powerful computation and communication capabilities, and enable numerous Mobile Crowdsourced Sensing (MCS) applications. Generally, an MCS system is composed of three components: A publisher of sensing tasks, crowd participants who complete the crowdsourced tasks for some kinds of rewards, and the crowdsourcing platform that facilitates the interaction between publishers and crowd participants. Incentives are a fundamental issue in MCS. This paper proposes an integrated incentive framework for MCS, which appropriately utilizes three widely used incentive methods: reverse auction, gamification, and reputation updating. Firstly, a reverse-Auction-based two-round participant selection mechanism is proposed to incentivize crowds to actively participate and provide high-quality sensing data. Secondly, in order to avoid untruthful publisher feedback about sensing-data quality, a gamification-based verification mechanism is designed to evaluate the truthfulness of the publisher's feedback. Finally, the platform updates the reputation of both participants and publishers based on their corresponding behaviors. This integrated incentive mechanism can motivate participants to provide high-quality sensed contents, stimulate publishers to give truthful feedback, and make the platform profitable.

Original languageEnglish
Article number7442498
Pages (from-to)146-156
Number of pages11
JournalTsinghua Science and Technology
Volume21
Issue number2
DOIs
Publication statusPublished - 2016 Apr

Keywords

  • gamification
  • incentive mechanism
  • mobile crowdsourced sensing
  • reputation updating
  • reverse auction

ASJC Scopus subject areas

  • General

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