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Allocating Heterogeneous Tasks in Participatory Sensing with Diverse Participant-Side Factors

Research output: Contribution to journalJournal article

Published

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Allocating Heterogeneous Tasks in Participatory Sensing with Diverse Participant-Side Factors. / Wang, Jiangtao; Wang, Feng; Wang, Yasha; Zhang, Daqing; Lim, Brian Y.; Wang, Leye.

In: IEEE Transactions on Mobile Computing, Vol. 18, No. 9, 10.09.2019, p. 1979-1991.

Research output: Contribution to journalJournal article

Harvard

Wang, J, Wang, F, Wang, Y, Zhang, D, Lim, BY & Wang, L 2019, 'Allocating Heterogeneous Tasks in Participatory Sensing with Diverse Participant-Side Factors', IEEE Transactions on Mobile Computing, vol. 18, no. 9, pp. 1979-1991. https://doi.org/10.1109/TMC.2018.2869387

APA

Wang, J., Wang, F., Wang, Y., Zhang, D., Lim, B. Y., & Wang, L. (2019). Allocating Heterogeneous Tasks in Participatory Sensing with Diverse Participant-Side Factors. IEEE Transactions on Mobile Computing, 18(9), 1979-1991. https://doi.org/10.1109/TMC.2018.2869387

Vancouver

Wang J, Wang F, Wang Y, Zhang D, Lim BY, Wang L. Allocating Heterogeneous Tasks in Participatory Sensing with Diverse Participant-Side Factors. IEEE Transactions on Mobile Computing. 2019 Sep 10;18(9):1979-1991. https://doi.org/10.1109/TMC.2018.2869387

Author

Wang, Jiangtao ; Wang, Feng ; Wang, Yasha ; Zhang, Daqing ; Lim, Brian Y. ; Wang, Leye. / Allocating Heterogeneous Tasks in Participatory Sensing with Diverse Participant-Side Factors. In: IEEE Transactions on Mobile Computing. 2019 ; Vol. 18, No. 9. pp. 1979-1991.

Bibtex

@article{e0afee864b184721b733d615f35a455b,
title = "Allocating Heterogeneous Tasks in Participatory Sensing with Diverse Participant-Side Factors",
abstract = "This paper proposes a novel task allocation framework, PSTasker, for participatory sensing (PS), which aims to maximize the overall system utility on PS platform by coordinating the allocation of multiple tasks. While existing studies mainly optimize the task allocation from the perspective of the task organizer (e.g., maximizing coverage or minimizing incentive cost), PSTasker further considers diverse factors on the participants' side, including user work bandwidth, user availability, devices' sensor configuration, task completion likelihood, and mobility pattern. Furthermore, by considering the heterogeneity in three dimensions (i.e., task, time and space), it adopts a novel model to measure task sensing quality and overall system utility. In PSTasker, it first calculates the utlity of a given task allocation plan by jointly fusing different participant-side factors into one unified estimation function, and then employs an iterative greedy process to optimize the task allocation. Extensive evaluations based on real-world mobility traces demonstrate that PSTasker outperforms the baseline methods under various settings.",
keywords = "Bandwidth, mobile crowd sensing, Mobile handsets, Monitoring, participant-side factors, Participatory sensing, Poles and towers, Resource management, Sensors, task allocation, Task analysis",
author = "Jiangtao Wang and Feng Wang and Yasha Wang and Daqing Zhang and Lim, {Brian Y.} and Leye Wang",
note = "{\textcopyright}2018 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. ",
year = "2019",
month = sep,
day = "10",
doi = "10.1109/TMC.2018.2869387",
language = "English",
volume = "18",
pages = "1979--1991",
journal = "IEEE Transactions on Mobile Computing",
issn = "1536-1233",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
number = "9",

}

RIS

TY - JOUR

T1 - Allocating Heterogeneous Tasks in Participatory Sensing with Diverse Participant-Side Factors

AU - Wang, Jiangtao

AU - Wang, Feng

AU - Wang, Yasha

AU - Zhang, Daqing

AU - Lim, Brian Y.

AU - Wang, Leye

N1 - ©2018 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.

PY - 2019/9/10

Y1 - 2019/9/10

N2 - This paper proposes a novel task allocation framework, PSTasker, for participatory sensing (PS), which aims to maximize the overall system utility on PS platform by coordinating the allocation of multiple tasks. While existing studies mainly optimize the task allocation from the perspective of the task organizer (e.g., maximizing coverage or minimizing incentive cost), PSTasker further considers diverse factors on the participants' side, including user work bandwidth, user availability, devices' sensor configuration, task completion likelihood, and mobility pattern. Furthermore, by considering the heterogeneity in three dimensions (i.e., task, time and space), it adopts a novel model to measure task sensing quality and overall system utility. In PSTasker, it first calculates the utlity of a given task allocation plan by jointly fusing different participant-side factors into one unified estimation function, and then employs an iterative greedy process to optimize the task allocation. Extensive evaluations based on real-world mobility traces demonstrate that PSTasker outperforms the baseline methods under various settings.

AB - This paper proposes a novel task allocation framework, PSTasker, for participatory sensing (PS), which aims to maximize the overall system utility on PS platform by coordinating the allocation of multiple tasks. While existing studies mainly optimize the task allocation from the perspective of the task organizer (e.g., maximizing coverage or minimizing incentive cost), PSTasker further considers diverse factors on the participants' side, including user work bandwidth, user availability, devices' sensor configuration, task completion likelihood, and mobility pattern. Furthermore, by considering the heterogeneity in three dimensions (i.e., task, time and space), it adopts a novel model to measure task sensing quality and overall system utility. In PSTasker, it first calculates the utlity of a given task allocation plan by jointly fusing different participant-side factors into one unified estimation function, and then employs an iterative greedy process to optimize the task allocation. Extensive evaluations based on real-world mobility traces demonstrate that PSTasker outperforms the baseline methods under various settings.

KW - Bandwidth

KW - mobile crowd sensing

KW - Mobile handsets

KW - Monitoring

KW - participant-side factors

KW - Participatory sensing

KW - Poles and towers

KW - Resource management

KW - Sensors

KW - task allocation

KW - Task analysis

U2 - 10.1109/TMC.2018.2869387

DO - 10.1109/TMC.2018.2869387

M3 - Journal article

AN - SCOPUS:85053161953

VL - 18

SP - 1979

EP - 1991

JO - IEEE Transactions on Mobile Computing

JF - IEEE Transactions on Mobile Computing

SN - 1536-1233

IS - 9

ER -