Computation Offloading and Trajectory Design for UAV-assisted Mobile Computing Systems

Sun, C; Ni, W; Wang, X

Computation Offloading and Trajectory Design for UAV-assisted Mobile Computing Systems

Sun, C Ni, W

Wang, X

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Publisher:: IEEE
Publication Type:: Conference Proceeding
Citation:: 2020 International Conference on Wireless Communications and Signal Processing (WCSP), 2020, 00, pp. 528-533
Issue Date:: 2020-12-28

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Field	Value	Language
dc.contributor.author	Sun, C
dc.contributor.author	Ni, W https://orcid.org/0000-0002-4933-594X
dc.contributor.author	Wang, X
dc.date	2020-10-21
dc.date.accessioned	2021-06-10T23:18:34Z
dc.date.available	2021-06-10T23:18:34Z
dc.date.issued	2020-12-28
dc.identifier.citation	2020 International Conference on Wireless Communications and Signal Processing (WCSP), 2020, 00, pp. 528-533
dc.identifier.isbn	978-1-7281-7236-1
dc.identifier.issn	2325-3746
dc.identifier.issn	2472-7628
dc.identifier.uri	http://hdl.handle.net/10453/149499
dc.description.abstract	This paper presents a new mobile computing framework where the smart terminals (STs) complete their tasks with the assistance of the unmanned aerial vehicle (UAV). While ensuring that the STs' tasks are processed by their deadlines, the UAV energy consumption is minimized by jointly optimizing the offloading time, offloading volume, as well as the CPU frequency and trajectory of the UAV. We establish the specific geometric condition of the UAV altitude and STs locations under which the problem of interest exhibits convexity, and propose an alternating optimization algorithm to obtain the globally optimal solution. In other cases, the problem is non-convex, which is challenging to solve. Leveraging successive convex approximation (SCA) technique, an efficient iterative algorithm is then developed to reap at least a quality solution satisfying the Karush-Kuhn-Tucker (KKT) conditions. Extensive simulation results demonstrate the merits of the proposed schemes.
dc.language	en
dc.publisher	IEEE
dc.relation.ispartof	2020 International Conference on Wireless Communications and Signal Processing (WCSP)
dc.relation.ispartof	International Conference on Wireless Communications and Signal Processing
dc.relation.isbasedon	10.1109/wcsp49889.2020.9299791
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	Computation Offloading and Trajectory Design for UAV-assisted Mobile Computing Systems
dc.type	Conference Proceeding
utslib.citation.volume	00
utslib.location.activity	Nanjing, China
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	2021-06-10T23:18:33Z
pubs.finish-date	2020-10-23
pubs.publication-status	Published
pubs.start-date	2020-10-21
pubs.volume	00

Abstract:

This paper presents a new mobile computing framework where the smart terminals (STs) complete their tasks with the assistance of the unmanned aerial vehicle (UAV). While ensuring that the STs' tasks are processed by their deadlines, the UAV energy consumption is minimized by jointly optimizing the offloading time, offloading volume, as well as the CPU frequency and trajectory of the UAV. We establish the specific geometric condition of the UAV altitude and STs locations under which the problem of interest exhibits convexity, and propose an alternating optimization algorithm to obtain the globally optimal solution. In other cases, the problem is non-convex, which is challenging to solve. Leveraging successive convex approximation (SCA) technique, an efficient iterative algorithm is then developed to reap at least a quality solution satisfying the Karush-Kuhn-Tucker (KKT) conditions. Extensive simulation results demonstrate the merits of the proposed schemes.

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http://hdl.handle.net/10453/149499