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Truthful Online Double Auctions for Mobile Crowdsourcing: An On-demand Service Strategy

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Published

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Truthful Online Double Auctions for Mobile Crowdsourcing: An On-demand Service Strategy. / Liu, S.; Yu, Y.; Guo, L. et al.
In: IEEE Internet of Things Journal, Vol. 9, No. 17, 01.09.2022, p. 16096 - 16112.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Harvard

Liu, S, Yu, Y, Guo, L, Yeoh, PL, Ni, Q, Vucetic, B & Li, Y 2022, 'Truthful Online Double Auctions for Mobile Crowdsourcing: An On-demand Service Strategy', IEEE Internet of Things Journal, vol. 9, no. 17, pp. 16096 - 16112. https://doi.org/10.1109/JIOT.2022.3151924

APA

Liu, S., Yu, Y., Guo, L., Yeoh, P. L., Ni, Q., Vucetic, B., & Li, Y. (2022). Truthful Online Double Auctions for Mobile Crowdsourcing: An On-demand Service Strategy. IEEE Internet of Things Journal, 9(17), 16096 - 16112. https://doi.org/10.1109/JIOT.2022.3151924

Vancouver

Liu S, Yu Y, Guo L, Yeoh PL, Ni Q, Vucetic B et al. Truthful Online Double Auctions for Mobile Crowdsourcing: An On-demand Service Strategy. IEEE Internet of Things Journal. 2022 Sept 1;9(17):16096 - 16112. Epub 2022 Feb 16. doi: 10.1109/JIOT.2022.3151924

Author

Liu, S. ; Yu, Y. ; Guo, L. et al. / Truthful Online Double Auctions for Mobile Crowdsourcing : An On-demand Service Strategy. In: IEEE Internet of Things Journal. 2022 ; Vol. 9, No. 17. pp. 16096 - 16112.

Bibtex

@article{cc331e214e1e43a5aff8c320afe7da74,
title = "Truthful Online Double Auctions for Mobile Crowdsourcing: An On-demand Service Strategy",
abstract = "Double auctions play a pivotal role in stimulating active participation of a large number of users comprising both task requesters and workers in mobile crowdsourcing. However, most existing studies have concentrated on designing offline two-sided auction mechanisms and supporting single-type tasks and fixed auction service models. Such works ignore the need of dynamic services and are unsuitable for large-scale crowdsourcing markets with extremely diverse demands (i.e., types and urgency degrees of tasks required by different requesters) and supplies (i.e., task skills and online durations of different workers). In this paper, we consider a practical crowdsourcing application with an on-demand service strategy. Especially, we innovatively design three online service models, namely online single-bid single-task (OSS), online single-bid multiple-task (OSM) and online multiple-bid multiple-task (OMM) models to accommodate diversified tasks and bidding demands for different users. Furthermore, to effectively allocate tasks and facilitate bidding, we propose a truthful online double auction mechanism for each service model based on the McAfee double auction. By doing so, each user can flexibly select auction service models and corresponding auction mechanisms according to their current interested tasks and online duration. To illustrate this, we present a three-demand example to explain the effectiveness of our on-demand service strategy in realistic crowdsourcing applications. Moreover, we theoretically prove that our mechanisms satisfy truthfulness, individual rationality, budget balance and consumer sovereignty. Through extensive simulations, we show that our mechanisms can accommodate the various demands of different users and improve social utility including platform utility and average user utility. IEEE",
keywords = "Biological system modeling, Crowdsourcing, Data models, Internet of Things, Mobile crowdsourcing, Nickel, on-demand service., online double auction, Resource management, Task analysis, truthful mechanism design, Biological systems, Commerce, Internet of things, Job analysis, Machine design, Double auction, On-demand service., On-demand services, Online double auction, Service modeling, Truthful mechanism designs, Budget control",
author = "S. Liu and Y. Yu and L. Guo and P.L. Yeoh and Q. Ni and B. Vucetic and Y. Li",
note = "{\textcopyright}2022 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 = "2022",
month = sep,
day = "1",
doi = "10.1109/JIOT.2022.3151924",
language = "English",
volume = "9",
pages = "16096 -- 16112",
journal = "IEEE Internet of Things Journal",
issn = "2327-4662",
publisher = "IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC",
number = "17",

}

RIS

TY - JOUR

T1 - Truthful Online Double Auctions for Mobile Crowdsourcing

T2 - An On-demand Service Strategy

AU - Liu, S.

AU - Yu, Y.

AU - Guo, L.

AU - Yeoh, P.L.

AU - Ni, Q.

AU - Vucetic, B.

AU - Li, Y.

N1 - ©2022 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 - 2022/9/1

Y1 - 2022/9/1

N2 - Double auctions play a pivotal role in stimulating active participation of a large number of users comprising both task requesters and workers in mobile crowdsourcing. However, most existing studies have concentrated on designing offline two-sided auction mechanisms and supporting single-type tasks and fixed auction service models. Such works ignore the need of dynamic services and are unsuitable for large-scale crowdsourcing markets with extremely diverse demands (i.e., types and urgency degrees of tasks required by different requesters) and supplies (i.e., task skills and online durations of different workers). In this paper, we consider a practical crowdsourcing application with an on-demand service strategy. Especially, we innovatively design three online service models, namely online single-bid single-task (OSS), online single-bid multiple-task (OSM) and online multiple-bid multiple-task (OMM) models to accommodate diversified tasks and bidding demands for different users. Furthermore, to effectively allocate tasks and facilitate bidding, we propose a truthful online double auction mechanism for each service model based on the McAfee double auction. By doing so, each user can flexibly select auction service models and corresponding auction mechanisms according to their current interested tasks and online duration. To illustrate this, we present a three-demand example to explain the effectiveness of our on-demand service strategy in realistic crowdsourcing applications. Moreover, we theoretically prove that our mechanisms satisfy truthfulness, individual rationality, budget balance and consumer sovereignty. Through extensive simulations, we show that our mechanisms can accommodate the various demands of different users and improve social utility including platform utility and average user utility. IEEE

AB - Double auctions play a pivotal role in stimulating active participation of a large number of users comprising both task requesters and workers in mobile crowdsourcing. However, most existing studies have concentrated on designing offline two-sided auction mechanisms and supporting single-type tasks and fixed auction service models. Such works ignore the need of dynamic services and are unsuitable for large-scale crowdsourcing markets with extremely diverse demands (i.e., types and urgency degrees of tasks required by different requesters) and supplies (i.e., task skills and online durations of different workers). In this paper, we consider a practical crowdsourcing application with an on-demand service strategy. Especially, we innovatively design three online service models, namely online single-bid single-task (OSS), online single-bid multiple-task (OSM) and online multiple-bid multiple-task (OMM) models to accommodate diversified tasks and bidding demands for different users. Furthermore, to effectively allocate tasks and facilitate bidding, we propose a truthful online double auction mechanism for each service model based on the McAfee double auction. By doing so, each user can flexibly select auction service models and corresponding auction mechanisms according to their current interested tasks and online duration. To illustrate this, we present a three-demand example to explain the effectiveness of our on-demand service strategy in realistic crowdsourcing applications. Moreover, we theoretically prove that our mechanisms satisfy truthfulness, individual rationality, budget balance and consumer sovereignty. Through extensive simulations, we show that our mechanisms can accommodate the various demands of different users and improve social utility including platform utility and average user utility. IEEE

KW - Biological system modeling

KW - Crowdsourcing

KW - Data models

KW - Internet of Things

KW - Mobile crowdsourcing

KW - Nickel

KW - on-demand service.

KW - online double auction

KW - Resource management

KW - Task analysis

KW - truthful mechanism design

KW - Biological systems

KW - Commerce

KW - Internet of things

KW - Job analysis

KW - Machine design

KW - Double auction

KW - On-demand service.

KW - On-demand services

KW - Online double auction

KW - Service modeling

KW - Truthful mechanism designs

KW - Budget control

U2 - 10.1109/JIOT.2022.3151924

DO - 10.1109/JIOT.2022.3151924

M3 - Journal article

VL - 9

SP - 16096

EP - 16112

JO - IEEE Internet of Things Journal

JF - IEEE Internet of Things Journal

SN - 2327-4662

IS - 17

ER -