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

Wang, Jiangtao and Wang, Leye and Wang, Yasha and Zhang, Daqing and Kong, Linghe (2018) Task Allocation in Mobile Crowd Sensing:State-of-the-Art and Future Opportunities. IEEE Internet of Things Journal, 5 (5). pp. 3747-3757. ISSN 2327-4662

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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.

Item Type:
Journal Article
Journal or Publication Title:
IEEE Internet of Things Journal
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/1700/1705
Subjects:
ID Code:
133108
Deposited By:
Deposited On:
25 Apr 2019 12:55
Refereed?:
Yes
Published?:
Published
Last Modified:
23 Sep 2020 05:13