Task Allocation in Mobile Crowd Sensing: State-of-the-Art and Future Opportunities

Jiangtao Wang, Leye Wang, Yasha Wang, Daqing Zhang, Linghe Kong

Research output: Contribution to journalReview article

22 Citations (Scopus)

Abstract

Mobile crowd sensing (MCS) is the special case of crowdsourcing, which leverages the smartphones with various embedded sensors and user's mobility to sense diverse phenomenon in a city. Task allocation is a fundamental research issue in MCS, which is crucial for the efficiency and effectiveness of MCS applications. In this paper, we specifically focus on the task allocation in MCS systems. We first present the unique features of MCS allocation compared to generic crowdsourcing, and then provide a comprehensive review for diversifying problem formulation and allocation algorithms together with future research opportunities.

Original languageEnglish
Pages (from-to)3747 - 3757
Number of pages11
JournalIEEE Internet of Things Journal
Volume5
Issue number5
Early online date8 Aug 2018
DOIs
Publication statusPublished - 1 Oct 2018
Externally publishedYes

Keywords

  • Crowdsourcing
  • mobile crowd sensing (MCS)
  • task allocation

Fingerprint Dive into the research topics of 'Task Allocation in Mobile Crowd Sensing: State-of-the-Art and Future Opportunities'. Together they form a unique fingerprint.

  • Cite this