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

Research output: Contribution to Journal/Magazine › Review article › peer-review

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Task Allocation in Mobile Crowd Sensing: State-of-the-Art and Future Opportunities. / Wang, Jiangtao; Wang, Leye; Wang, Yasha et al.
In: IEEE Internet of Things Journal, Vol. 5, No. 5, 01.10.2018, p. 3747-3757.

Research output: Contribution to Journal/Magazine › Review article › peer-review

Harvard

Wang, J, Wang, L, Wang, Y, Zhang, D & Kong, L 2018, 'Task Allocation in Mobile Crowd Sensing: State-of-the-Art and Future Opportunities', IEEE Internet of Things Journal, vol. 5, no. 5, pp. 3747-3757. https://doi.org/10.1109/JIOT.2018.2864341

APA

Wang, J., Wang, L., Wang, Y., Zhang, D., & Kong, L. (2018). Task Allocation in Mobile Crowd Sensing: State-of-the-Art and Future Opportunities. IEEE Internet of Things Journal, 5(5), 3747-3757. https://doi.org/10.1109/JIOT.2018.2864341

Vancouver

Wang J, Wang L, Wang Y, Zhang D, Kong L. Task Allocation in Mobile Crowd Sensing: State-of-the-Art and Future Opportunities. IEEE Internet of Things Journal. 2018 Oct 1;5(5):3747-3757. Epub 2018 Aug 8. doi: 10.1109/JIOT.2018.2864341

Author

Wang, Jiangtao ; Wang, Leye ; Wang, Yasha et al. / Task Allocation in Mobile Crowd Sensing : State-of-the-Art and Future Opportunities. In: IEEE Internet of Things Journal. 2018 ; Vol. 5, No. 5. pp. 3747-3757.

Bibtex

@article{83fde409d3b243649efff32c2ee493c3,
title = "Task Allocation in Mobile Crowd Sensing: State-of-the-Art and Future Opportunities",
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.",
keywords = "Crowdsourcing, mobile crowd sensing (MCS), task allocation, PARTICIPANT SELECTION, INTERNET, ASSIGNMENT, FRAMEWORK, PRIVACY, BUDGET",
author = "Jiangtao Wang and Leye Wang and Yasha Wang and Daqing Zhang and Linghe Kong",
year = "2018",
month = oct,
day = "1",
doi = "10.1109/JIOT.2018.2864341",
language = "English",
volume = "5",
pages = "3747--3757",
journal = "IEEE Internet of Things Journal",
issn = "2327-4662",
publisher = "IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC",
number = "5",

}

RIS

TY - JOUR

T1 - Task Allocation in Mobile Crowd Sensing

T2 - State-of-the-Art and Future Opportunities

AU - Wang, Jiangtao

AU - Wang, Leye

AU - Wang, Yasha

AU - Zhang, Daqing

AU - Kong, Linghe

PY - 2018/10/1

Y1 - 2018/10/1

N2 - 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.

AB - 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.

KW - Crowdsourcing

KW - mobile crowd sensing (MCS)

KW - task allocation

KW - PARTICIPANT SELECTION

KW - INTERNET

KW - ASSIGNMENT

KW - FRAMEWORK

KW - PRIVACY

KW - BUDGET

U2 - 10.1109/JIOT.2018.2864341

DO - 10.1109/JIOT.2018.2864341

M3 - Review article

VL - 5

SP - 3747

EP - 3757

JO - IEEE Internet of Things Journal

JF - IEEE Internet of Things Journal

SN - 2327-4662

IS - 5

ER -