Squadron: Incentivizing Quality-Aware Mission-Driven Crowd Sensing

Haiming Jin, Hongpeng Guo, Klara Nahrstedt

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Recent years have witnessed the success of mobile crowd sensing systems, which outsource sensory data collection to the public crowd equipped with various mobile devices in a wide spectrum of civilian applications. We envision that crowd sensing could as well be very useful in a whole host of mission-driven scenarios, such as peacekeeping operations, non-combatant evacuations, and humanitarian missions. However, the power of crowd sensing could not be fully unleashed in mission-driven crowd sensing (MiCS) systems, unless workers are effectively incentivized to participate. Therefore, in this paper, taking into consideration workers' diverse quality of information (QoI), we propose Squadron, a quality-aware incentive mechanism for MiCS systems. Squadron adopts the reverse auction framework. It approximately minimizes the platform's total payment for worker recruiting in a computationally efficient manner, and recruits workers who potentially could provide high quality data. Furthermore, it also satisfies the desirable properties of truth-fulness and individual rationality. Through rigorous theoretical analysis, as well as extensive simulations, we validate the various aforementioned desirable properties held by Squadron.

Original languageEnglish (US)
Title of host publication2018 21st International Conference on Information Fusion, FUSION 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2306-2313
Number of pages8
ISBN (Print)9780996452762
DOIs
StatePublished - Sep 5 2018
Event21st International Conference on Information Fusion, FUSION 2018 - Cambridge, United Kingdom
Duration: Jul 10 2018Jul 13 2018

Other

Other21st International Conference on Information Fusion, FUSION 2018
CountryUnited Kingdom
CityCambridge
Period7/10/187/13/18

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Keywords

  • incentive mechanism
  • mission-driven crowd sensing
  • quality of information

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Statistics, Probability and Uncertainty
  • Instrumentation

Cite this

Jin, H., Guo, H., & Nahrstedt, K. (2018). Squadron: Incentivizing Quality-Aware Mission-Driven Crowd Sensing. In 2018 21st International Conference on Information Fusion, FUSION 2018 (pp. 2306-2313). [8455374] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.23919/ICIF.2018.8455374