Files in this item
Task offloading engine for heterogeneous mobile Clouds
Item metadata
dc.contributor.author | Sulaiman, Dawand Jalil | |
dc.contributor.author | Barker, Adam David | |
dc.date.accessioned | 2017-02-14T11:30:15Z | |
dc.date.available | 2017-02-14T11:30:15Z | |
dc.date.issued | 2016-12-01 | |
dc.identifier.citation | Sulaiman , D J & Barker , A D 2016 , Task offloading engine for heterogeneous mobile Clouds . in Proceedings of The 8th EAI International Conference on Mobile Computing, Applications and Services . ACM , 8th EAI International Conference on Mobile Computing, Applications and Services , Cambridge , United Kingdom , 30/11/16 . https://doi.org/10.4108/eai.30-11-2016.2267048 | en |
dc.identifier.citation | conference | en |
dc.identifier.other | PURE: 249028246 | |
dc.identifier.other | PURE UUID: 3b105f2c-b686-42fb-9625-23e75cc387ef | |
dc.identifier.other | Scopus: 85041368369 | |
dc.identifier.other | ORCID: /0000-0001-9884-8015/work/58056062 | |
dc.identifier.uri | http://hdl.handle.net/10023/10292 | |
dc.description.abstract | The limitations in computational resources and battery power of mobile devices led to the concept of offloading compute-intensive tasks to powerful devices. We have developed a framework to offload tasks from a mobile device to other nearby heterogeneous devices. It contains an offloading engine to selectively choose the target devices for the execution of the offloaded tasks to address optimal scheduling across devices with diverse capabilities. Our initial conducted runtime measurements show the feasibility of this concept. As preliminary results, we show that offloading compute intensive tasks from a device with less computational capability to a set of nearby more powerful devices can reduce the overall computational time by approximately 50%. | |
dc.format.extent | 2 | |
dc.language.iso | eng | |
dc.publisher | ACM | |
dc.relation.ispartof | Proceedings of The 8th EAI International Conference on Mobile Computing, Applications and Services | en |
dc.rights | © 2016, EAI. This work has been made available online in accordance with the publisher’s policies. This is the author created, accepted version manuscript following peer review and may differ slightly from the final published version. The final published version of this work is available at www.eudl.eu / http://dx.doi.org/10.4108/eai.30-11-2016.2267048 | en |
dc.subject | Mobile Clouds | en |
dc.subject | Task offloading | en |
dc.subject | Heterogeneity | en |
dc.subject | QA75 Electronic computers. Computer science | en |
dc.subject | QA76 Computer software | en |
dc.subject | TA Engineering (General). Civil engineering (General) | en |
dc.subject | NDAS | en |
dc.subject.lcc | QA75 | en |
dc.subject.lcc | QA76 | en |
dc.subject.lcc | TA | en |
dc.title | Task offloading engine for heterogeneous mobile Clouds | en |
dc.type | Conference item | en |
dc.description.version | Postprint | en |
dc.contributor.institution | University of St Andrews. School of Computer Science | en |
dc.identifier.doi | https://doi.org/10.4108/eai.30-11-2016.2267048 |
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.