Loop Parallelism Maximization for Multimedia Data Processing in Mobile Vehicular Clouds

Qiu, M; Dai, W; Vasilakos, AV

Loop Parallelism Maximization for Multimedia Data Processing in Mobile Vehicular Clouds

Qiu, M Dai, W Vasilakos, AV

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Publication Type:: Journal Article
Citation:: IEEE Transactions on Cloud Computing, 2019, 7 (1), pp. 250 - 258
Issue Date:: 2019-01-01

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Field	Value	Language
dc.contributor.author	Qiu, M	en_US
dc.contributor.author	Dai, W	en_US
dc.contributor.author	Vasilakos, AV https://orcid.org/0000-0003-1902-9877	en_US
dc.date.accessioned	2020-04-19T21:39:50Z
dc.date.available	2020-04-19T21:39:50Z
dc.date.issued	2019-01-01	en_US
dc.identifier.citation	IEEE Transactions on Cloud Computing, 2019, 7 (1), pp. 250 - 258	en_US
dc.identifier.uri	http://hdl.handle.net/10453/140093
dc.description.abstract	© 2013 IEEE. Mobile vehicular cloud has become popular with the rapid development of cloud computing and mobile computing. Nested loops are usually the most critical part in multimedia and high performance Digital Signal Processing (DSP) systems which are widely used in vehicular applications and systems. In order to further explore the parallelism in nested loops, we study how to maximize the system performance with considering the energy reduction for applications on Chip Multiprocessor (CMP) architectures. We propose an algorithm Energy-Aware Loop Parallelism Maximization (EALPM) to maximize the system performance with the consideration of energy reduction for applications with multidimensional nested loops. Our experiment shows that using the EALPM algorithm significantly improves both performance and energy consumption on average in comparision to other algorithms.	en_US
dc.relation.ispartof	IEEE Transactions on Cloud Computing	en_US
dc.relation.isbasedon	10.1109/TCC.2016.2607708	en_US
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	Loop Parallelism Maximization for Multimedia Data Processing in Mobile Vehicular Clouds	en_US
dc.type	Journal Article
utslib.citation.volume	1	en_US
utslib.citation.volume	7	en_US
utslib.for	0805 Distributed Computing	en_US
utslib.for	0806 Information Systems	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
utslib.copyright.status	closed_access	*
pubs.issue	1	en_US
pubs.publication-status	Published	en_US
pubs.volume	7	en_US

Abstract:

© 2013 IEEE. Mobile vehicular cloud has become popular with the rapid development of cloud computing and mobile computing. Nested loops are usually the most critical part in multimedia and high performance Digital Signal Processing (DSP) systems which are widely used in vehicular applications and systems. In order to further explore the parallelism in nested loops, we study how to maximize the system performance with considering the energy reduction for applications on Chip Multiprocessor (CMP) architectures. We propose an algorithm Energy-Aware Loop Parallelism Maximization (EALPM) to maximize the system performance with the consideration of energy reduction for applications with multidimensional nested loops. Our experiment shows that using the EALPM algorithm significantly improves both performance and energy consumption on average in comparision to other algorithms.

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http://hdl.handle.net/10453/140093