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Article: On Energy-Efficient Offloading in Mobile Cloud for Real-Time Video Applications

TitleOn Energy-Efficient Offloading in Mobile Cloud for Real-Time Video Applications
Authors
Keywordsmobile cloud
Energy efficiency
offloading
video
Issue Date2017
Citation
IEEE Transactions on Circuits and Systems for Video Technology, 2017, v. 27, n. 1, p. 170-181 How to Cite?
Abstract© 1991-2012 IEEE. Batteries of modern mobile devices remain severely limited in capacity, which makes energy consumption a key concern for mobile applications, particularly for the computation-intensive video applications. Mobile devices can save energy by offloading computation tasks to the cloud, yet the energy gain must exceed the additional communication cost for cloud migration to be beneficial. The situation is further complicated by real-Time video applications that have stringent delay and bandwidth constraints. In this paper, we closely examine the performance and energy efficiency of representative mobile cloud applications under dynamic wireless network channels and state-of-The-Art mobile platforms. We identify the unique challenges of and opportunities for offloading real-Time video applications and develop a generic model for energy-efficient computation offloading accordingly in this context. We propose a scheduling algorithm that makes adaptive offloading decisions in fine granularity in dynamic wireless network conditions and verify its effectiveness through trace-driven simulations. We further present case studies with advanced mobile platforms and practical applications to demonstrate the superiority of our solution and the substantial gain of our approach over baseline approaches.
Persistent Identifierhttp://hdl.handle.net/10722/281456
ISSN
2020 Impact Factor: 4.685
2020 SCImago Journal Rankings: 0.873
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorZhang, Lei-
dc.contributor.authorFu, Di-
dc.contributor.authorLiu, Jiangchuan-
dc.contributor.authorNgai, Edith Cheuk Han-
dc.contributor.authorZhu, Wenwu-
dc.date.accessioned2020-03-13T10:37:55Z-
dc.date.available2020-03-13T10:37:55Z-
dc.date.issued2017-
dc.identifier.citationIEEE Transactions on Circuits and Systems for Video Technology, 2017, v. 27, n. 1, p. 170-181-
dc.identifier.issn1051-8215-
dc.identifier.urihttp://hdl.handle.net/10722/281456-
dc.description.abstract© 1991-2012 IEEE. Batteries of modern mobile devices remain severely limited in capacity, which makes energy consumption a key concern for mobile applications, particularly for the computation-intensive video applications. Mobile devices can save energy by offloading computation tasks to the cloud, yet the energy gain must exceed the additional communication cost for cloud migration to be beneficial. The situation is further complicated by real-Time video applications that have stringent delay and bandwidth constraints. In this paper, we closely examine the performance and energy efficiency of representative mobile cloud applications under dynamic wireless network channels and state-of-The-Art mobile platforms. We identify the unique challenges of and opportunities for offloading real-Time video applications and develop a generic model for energy-efficient computation offloading accordingly in this context. We propose a scheduling algorithm that makes adaptive offloading decisions in fine granularity in dynamic wireless network conditions and verify its effectiveness through trace-driven simulations. We further present case studies with advanced mobile platforms and practical applications to demonstrate the superiority of our solution and the substantial gain of our approach over baseline approaches.-
dc.languageeng-
dc.relation.ispartofIEEE Transactions on Circuits and Systems for Video Technology-
dc.subjectmobile cloud-
dc.subjectEnergy efficiency-
dc.subjectoffloading-
dc.subjectvideo-
dc.titleOn Energy-Efficient Offloading in Mobile Cloud for Real-Time Video Applications-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1109/TCSVT.2016.2539690-
dc.identifier.scopuseid_2-s2.0-85009723951-
dc.identifier.volume27-
dc.identifier.issue1-
dc.identifier.spage170-
dc.identifier.epage181-
dc.identifier.isiWOS:000393796500015-
dc.identifier.issnl1051-8215-

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