DATS: Dispersive stable task scheduling in heterogeneous fog networks

Liu, Z; Yang, X; Yang, Y; Wang, K; Mao, G

DATS: Dispersive stable task scheduling in heterogeneous fog networks

Liu, Z Yang, X Yang, Y Wang, K Mao, G

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Publication Type:: Journal Article
Citation:: IEEE Internet of Things Journal, 2019, 6 (2), pp. 3423 - 3436
Issue Date:: 2019-04-01

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Field	Value	Language
dc.contributor.author	Liu, Z	en_US
dc.contributor.author	Yang, X	en_US
dc.contributor.author	Yang, Y	en_US
dc.contributor.author	Wang, K	en_US
dc.contributor.author	Mao, G https://orcid.org/0000-0002-3598-4949	en_US
dc.date.issued	2019-04-01	en_US
dc.identifier.citation	IEEE Internet of Things Journal, 2019, 6 (2), pp. 3423 - 3436	en_US
dc.identifier.uri	http://hdl.handle.net/10453/135048
dc.description.abstract	© 2014 IEEE. Fog computing has risen as a promising architecture for future Internet of Things, 5G and embedded artificial intelligence applications with stringent service delay requirements along the cloud to things continuum. For a typical fog network consisting of heterogeneous fog nodes (FNs) with different computing resources and communication capabilities, how to effectively schedule complex computation tasks to multiple FNs in the neighborhood to achieve minimal service delay is a fundamental challenge. To tackle this problem, a new concept named processing efficiency (PE) is first defined to incorporate computing resources and communication capacities. Further, to minimize service delay in heterogeneous fog networks, a scalable, stable, and decentralized algorithm, namely dispersive stable task scheduling (DATS), is proposed and evaluated, which consists of two key components: 1) a PE-based progressive computing resources competition and 2) a QoE-oriented synchronized task scheduling. Theoretical proofs and simulation results show that the proposed DATS algorithm can achieve effective tradeoff between computing resources and communication capabilities, thus significantly reducing service delay in heterogeneous fog networks.	en_US
dc.relation.ispartof	IEEE Internet of Things Journal	en_US
dc.relation.isbasedon	10.1109/JIOT.2018.2884720	en_US
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	DATS: Dispersive stable task scheduling in heterogeneous fog networks	en_US
dc.type	Journal Article
utslib.citation.volume	2	en_US
utslib.citation.volume	6	en_US
utslib.for	0906 Electrical and Electronic Engineering	en_US
utslib.for	0805 Distributed Computing	en_US
utslib.for	1005 Communications Technologies	en_US
pubs.embargo.period	Not known	en_US
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
pubs.organisational-group	/University of Technology Sydney/Strength - CRIN - Realtime Information Networks
utslib.copyright.status	closed_access	*
pubs.issue	2	en_US
pubs.publication-status	Published	en_US
pubs.volume	6	en_US

Abstract:

© 2014 IEEE. Fog computing has risen as a promising architecture for future Internet of Things, 5G and embedded artificial intelligence applications with stringent service delay requirements along the cloud to things continuum. For a typical fog network consisting of heterogeneous fog nodes (FNs) with different computing resources and communication capabilities, how to effectively schedule complex computation tasks to multiple FNs in the neighborhood to achieve minimal service delay is a fundamental challenge. To tackle this problem, a new concept named processing efficiency (PE) is first defined to incorporate computing resources and communication capacities. Further, to minimize service delay in heterogeneous fog networks, a scalable, stable, and decentralized algorithm, namely dispersive stable task scheduling (DATS), is proposed and evaluated, which consists of two key components: 1) a PE-based progressive computing resources competition and 2) a QoE-oriented synchronized task scheduling. Theoretical proofs and simulation results show that the proposed DATS algorithm can achieve effective tradeoff between computing resources and communication capabilities, thus significantly reducing service delay in heterogeneous fog networks.

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http://hdl.handle.net/10453/135048