Internet of vehicles for e-health applications: A potential game for optimal network capacity

Lin, D; Tang, Y; Labeau, F; Yao, Y; Imran, M; Vasilakos, AV

Internet of vehicles for e-health applications: A potential game for optimal network capacity

Lin, D Tang, Y Labeau, F Yao, Y Imran, M Vasilakos, AV

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Publisher:: Institute of Electrical and Electronics Engineers
Publication Type:: Journal Article
Citation:: IEEE Systems Journal, 2017, 11, (3), pp. 1888-1896
Issue Date:: 2017-09-01

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Field	Value	Language
dc.contributor.author	Lin, D
dc.contributor.author	Tang, Y
dc.contributor.author	Labeau, F
dc.contributor.author	Yao, Y
dc.contributor.author	Imran, M
dc.contributor.author	Vasilakos, AV
dc.date.accessioned	2022-08-23T02:19:09Z
dc.date.available	2022-08-23T02:19:09Z
dc.date.issued	2017-09-01
dc.identifier.citation	IEEE Systems Journal, 2017, 11, (3), pp. 1888-1896
dc.identifier.issn	1932-8184
dc.identifier.issn	1937-9234
dc.identifier.uri	http://hdl.handle.net/10453/160719
dc.description.abstract	Wireless technologies are pervasive to support ubiquitous healthcare applications. However, a critical issue of using wireless communications under a healthcare scenario rests at the electromagnetic interference (EMI) caused by RF transmission, and a high level of EMI may lead to a critical malfunction of medical sensors. In view of EMI on medical sensors, we propose a power control algorithm under a noncooperative game theoretic framework to schedule data transmission. Our objective is to ensure that the noncooperative game of power control can achieve a network-level objective - the optimal network capacity, although the wireless users are selfish and only interested in optimizing their own channel capacity. To obtain this objective, we show that our proposed noncooperative game is a potential game and propose the best-response-dynamics algorithm which can ensure that the game strategy of each user is induced to the optimal solution to the problem of network-level optimal capacity. Numerical results illustrate that the proposed algorithm can achieve an enhancement of 8% of network performance than the existing algorithm against the variations of mobile hospital environments.
dc.language	English
dc.publisher	Institute of Electrical and Electronics Engineers
dc.relation.ispartof	IEEE Systems Journal
dc.relation.isbasedon	10.1109/JSYST.2015.2441720
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	0906 Electrical and Electronic Engineering
dc.subject.classification	Operations Research
dc.title	Internet of vehicles for e-health applications: A potential game for optimal network capacity
dc.type	Journal Article
utslib.citation.volume	11
utslib.for	0906 Electrical and Electronic Engineering
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
utslib.copyright.status	closed_access	*
pubs.consider-herdc	false
dc.date.updated	2022-08-23T02:19:08Z
pubs.issue	3
pubs.publication-status	Published
pubs.volume	11
utslib.citation.issue	3

Abstract:

Wireless technologies are pervasive to support ubiquitous healthcare applications. However, a critical issue of using wireless communications under a healthcare scenario rests at the electromagnetic interference (EMI) caused by RF transmission, and a high level of EMI may lead to a critical malfunction of medical sensors. In view of EMI on medical sensors, we propose a power control algorithm under a noncooperative game theoretic framework to schedule data transmission. Our objective is to ensure that the noncooperative game of power control can achieve a network-level objective - the optimal network capacity, although the wireless users are selfish and only interested in optimizing their own channel capacity. To obtain this objective, we show that our proposed noncooperative game is a potential game and propose the best-response-dynamics algorithm which can ensure that the game strategy of each user is induced to the optimal solution to the problem of network-level optimal capacity. Numerical results illustrate that the proposed algorithm can achieve an enhancement of 8% of network performance than the existing algorithm against the variations of mobile hospital environments.

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http://hdl.handle.net/10453/160719