An Online Intelligent Task Pricing Mechanism Based on Reverse Auction in Mobile Crowdsensing Networks for the Internet of Things

Jia, B; Cen, H; Luo, X; Liu, S; Muhammad, K; Gandomi, AH; De Albuquerque, VHC

An Online Intelligent Task Pricing Mechanism Based on Reverse Auction in Mobile Crowdsensing Networks for the Internet of Things

Jia, B Cen, H Luo, X Liu, S Muhammad, K Gandomi, AH De Albuquerque, VHC

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Publisher:: IEEE
Publication Type:: Conference Proceeding
Citation:: 2021 IEEE Symposium Series on Computational Intelligence (SSCI), 2022, 00
Issue Date:: 2022

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Field	Value	Language
dc.contributor.author	Jia, B
dc.contributor.author	Cen, H
dc.contributor.author	Luo, X
dc.contributor.author	Liu, S
dc.contributor.author	Muhammad, K
dc.contributor.author	Gandomi, AH
dc.contributor.author	De Albuquerque, VHC
dc.date	2021-12-05
dc.date.accessioned	2023-04-06T03:16:40Z
dc.date.available	2023-04-06T03:16:40Z
dc.date.issued	2022
dc.identifier.citation	2021 IEEE Symposium Series on Computational Intelligence (SSCI), 2022, 00
dc.identifier.isbn	978-1-7281-9048-8
dc.identifier.uri	http://hdl.handle.net/10453/169290
dc.description.abstract	The Mobile Crowdsensing Network is a new data acquisition method, which is devoted to provide universal service for the Internet of Things, and it is also an important application field of Computational Intelligence. A reasonable task pricing mechanism can not only motivate more users to participate in the sensing task but also help the sustainable development of the platform. In view of the widespread problem that the fine pricing of perceived tasks in online scenes is not considered, an online intelligent task pricing mechanism based on reverse auction is proposed in this paper, which is combined with Computational Intelligence to ensure that the task price is determined in realtime through subject interaction. Task participants submit quotation information to the platform to obtain eligibility to participate in the task. The platform selects the arriving task participants and determines their remuneration by Reverse Auction strategy. The results show that the mechanism can improve the income of task participants, and encourage them to actively participate in sensing tasks.
dc.language	en
dc.publisher	IEEE
dc.relation.ispartof	2021 IEEE Symposium Series on Computational Intelligence (SSCI)
dc.relation.ispartof	IEEE Symposium Series on Computational Intelligence
dc.relation.isbasedon	10.1109/ssci50451.2021.9659901
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	An Online Intelligent Task Pricing Mechanism Based on Reverse Auction in Mobile Crowdsensing Networks for the Internet of Things
dc.type	Conference Proceeding
utslib.citation.volume	00
utslib.location.activity	Orlando, FL, USA
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
utslib.copyright.status	closed_access	*
pubs.consider-herdc	false
dc.date.updated	2023-04-06T03:16:38Z
pubs.finish-date	2021-12-07
pubs.place-of-publication	Piscataway, USA
pubs.publication-status	Published
pubs.start-date	2021-12-05
pubs.volume	00
dc.location	Piscataway, USA

Abstract:

The Mobile Crowdsensing Network is a new data acquisition method, which is devoted to provide universal service for the Internet of Things, and it is also an important application field of Computational Intelligence. A reasonable task pricing mechanism can not only motivate more users to participate in the sensing task but also help the sustainable development of the platform. In view of the widespread problem that the fine pricing of perceived tasks in online scenes is not considered, an online intelligent task pricing mechanism based on reverse auction is proposed in this paper, which is combined with Computational Intelligence to ensure that the task price is determined in realtime through subject interaction. Task participants submit quotation information to the platform to obtain eligibility to participate in the task. The platform selects the arriving task participants and determines their remuneration by Reverse Auction strategy. The results show that the mechanism can improve the income of task participants, and encourage them to actively participate in sensing tasks.

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http://hdl.handle.net/10453/169290