Offloading Energy Efficiency with Delay Constraint for Cooperative Mobile Edge Computing Networks

Vu, TT; Huynh, NV; Hoang, DT; Nguyen, DN; Dutkiewicz, E

Offloading Energy Efficiency with Delay Constraint for Cooperative Mobile Edge Computing Networks

Vu, TT

Huynh, NV Hoang, DT

Nguyen, DN

Dutkiewicz, E

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Publication Type:: Conference Proceeding
Citation:: 2018 IEEE Global Communications Conference, GLOBECOM 2018 - Proceedings, 2018
Issue Date:: 2018-01-01

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Field	Value	Language
dc.contributor.author	Vu, TT https://orcid.org/0000-0002-9826-3321	en_US
dc.contributor.author	Huynh, NV	en_US
dc.contributor.author	Hoang, DT https://orcid.org/0000-0002-9528-0863	en_US
dc.contributor.author	Nguyen, DN https://orcid.org/0000-0003-2659-8648	en_US
dc.contributor.author	Dutkiewicz, E https://orcid.org/0000-0002-4268-9286	en_US
dc.date.available	2020-12-05T18:08:23Z
dc.date.issued	2018-01-01	en_US
dc.identifier.citation	2018 IEEE Global Communications Conference, GLOBECOM 2018 - Proceedings, 2018	en_US
dc.identifier.isbn	9781538647271	en_US
dc.identifier.uri	http://hdl.handle.net/10453/131923
dc.description.abstract	© 2018 IEEE. We propose a novel edge computing network architecture that enables edge nodes to cooperate in sharing computing and radio resources to minimize the total energy consumption of mobile users while meeting their delay requirements. To find the optimal task offloading decisions for mobile users, we first formulate the joint task offloading and resource allocation optimization problem as a mixed integer non-linear programming (MINLP). The optimization involves both binary (offloading decisions) and real variables (resource allocations), making it an NP-hard and computational intractable problem. To circumvent, we relax the binary decision variables to transform the MINLP to a relaxed optimization problem with real variables. After proving that the relaxed problem is a convex one, we propose two solutions namely ROP and IBBA. ROP is adopted from the interior point method and IBBA is developed from the branch and bound algorithm. Through the numerical results, we show that our proposed approaches allow minimizing the total energy consumption and meet all delay requirements for mobile users.	en_US
dc.relation.ispartof	2018 IEEE Global Communications Conference, GLOBECOM 2018 - Proceedings	en_US
dc.relation.isbasedon	10.1109/GLOCOM.2018.8647856	en_US
dc.rights	info:eu-repo/semantics/openAccess
dc.title	Offloading Energy Efficiency with Delay Constraint for Cooperative Mobile Edge Computing Networks	en_US
dc.type	Conference Proceeding
utslib.for	0805 Distributed Computing	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 - GBDTC - Global Big Data Technologies
pubs.organisational-group	/University of Technology Sydney/Students
utslib.copyright.status	open_access	*
pubs.publication-status	Published	en_US

Abstract:

© 2018 IEEE. We propose a novel edge computing network architecture that enables edge nodes to cooperate in sharing computing and radio resources to minimize the total energy consumption of mobile users while meeting their delay requirements. To find the optimal task offloading decisions for mobile users, we first formulate the joint task offloading and resource allocation optimization problem as a mixed integer non-linear programming (MINLP). The optimization involves both binary (offloading decisions) and real variables (resource allocations), making it an NP-hard and computational intractable problem. To circumvent, we relax the binary decision variables to transform the MINLP to a relaxed optimization problem with real variables. After proving that the relaxed problem is a convex one, we propose two solutions namely ROP and IBBA. ROP is adopted from the interior point method and IBBA is developed from the branch and bound algorithm. Through the numerical results, we show that our proposed approaches allow minimizing the total energy consumption and meet all delay requirements for mobile users.

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http://hdl.handle.net/10453/131923