Files in this item
MAMoC-Android : Multisite Adaptive Computation Offloading for Android applications
Item metadata
dc.contributor.author | Sulaiman, Dawand Jalil | |
dc.contributor.author | Barker, Adam David | |
dc.date.accessioned | 2019-06-07T09:30:03Z | |
dc.date.available | 2019-06-07T09:30:03Z | |
dc.date.issued | 2019-05-13 | |
dc.identifier | 259229398 | |
dc.identifier | 857a832c-41f5-4ba3-92d4-8c3e90302f57 | |
dc.identifier | 85066506593 | |
dc.identifier | 000470058100008 | |
dc.identifier.citation | Sulaiman , D J & Barker , A D 2019 , MAMoC-Android : Multisite Adaptive Computation Offloading for Android applications . in 2019 7th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering (MobileCloud) . IEEE Computer Society , pp. 68-75 , 2019 7th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering , San Fransisco , California , United States , 4/04/19 . https://doi.org/10.1109/MobileCloud.2019.00017 | en |
dc.identifier.citation | conference | en |
dc.identifier.isbn | 9781728104645 | |
dc.identifier.isbn | 9781728104638 | |
dc.identifier.other | ORCID: /0000-0001-9884-8015/work/58056064 | |
dc.identifier.uri | https://hdl.handle.net/10023/17842 | |
dc.description.abstract | Computational offloading has been widely used to improve the performance of mobile applications and conserve the energy of mobile devices. Prior studies have primarily focused on a form of offloading where only a single server is considered as the offloading site. However, mobile devices now have access to a range of nearby mobile and fixed devices and multiple cloud providers. This paper proposes a method for multisite computation offloading in dynamic mobile cloud environments, in order to save energy and improve application execution time. Our proposed dynamic offloading decision algorithm takes into consideration the offloading score and records of past offloading executions to select the best candidate(s) for offloading. Multisite offloading execution achieves a greater reduction with respect to the completion time and energy consumption of mobiles when compared to local execution or a single-site offloading execution on a public cloud instance. | |
dc.format.extent | 8 | |
dc.format.extent | 343073 | |
dc.language.iso | eng | |
dc.publisher | IEEE Computer Society | |
dc.relation.ispartof | 2019 7th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering (MobileCloud) | en |
dc.subject | Mobile Clouds | en |
dc.subject | Multisite offloading | en |
dc.subject | Adaptive offloading | en |
dc.subject | Android apps | en |
dc.subject | Android offloading | en |
dc.subject | QA75 Electronic computers. Computer science | en |
dc.subject | T Technology | en |
dc.subject | Computer Science Applications | en |
dc.subject | NDAS | en |
dc.subject | SDG 7 - Affordable and Clean Energy | en |
dc.subject.lcc | QA75 | en |
dc.subject.lcc | T | en |
dc.title | MAMoC-Android : Multisite Adaptive Computation Offloading for Android applications | en |
dc.type | Conference item | en |
dc.contributor.sponsor | EPSRC | en |
dc.contributor.institution | University of St Andrews. School of Computer Science | en |
dc.identifier.doi | 10.1109/MobileCloud.2019.00017 | |
dc.identifier.grantnumber | EP/R010528/1 | en |
This item appears in the following Collection(s)
Items in the St Andrews Research Repository are protected by copyright, with all rights reserved, unless otherwise indicated.