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dc.contributor.authorLiu, Y
dc.contributor.authorFieldsend, JE
dc.contributor.authorMin, G
dc.date.accessioned2017-11-02T14:05:52Z
dc.date.issued2017-10-26
dc.description.abstractFog Computing (FC) is an emerging distributed computing platform aimed at bringing computation close to its data sources, which can reduce the latency and cost of delivering data to a remote cloud. This feature and related advantages are desirable for many Internet-of-Things applications, especially latency sensitive and mission intensive services. With comparisons to other computing technologies, the definition and architecture of FC are presented in this article. The framework of resource allocation for latency reduction combined with reliability, fault tolerance, privacy, and underlying optimization problems are also discussed. We then investigate an application scenario and conduct resource optimization by formulating the optimization problem and solving it via a Genetic Algorithm. The resulting analysis generates some important insights on the scalability of FC systems.en_GB
dc.description.sponsorshipThis work was supported by the Engineering and Physical Sciences Research Council [grant number EP/P020224/1] and the EU FP7 QUICK project under Grant Agreement No. PIRSES-GA-2013-612652. Yang Liu was supported by the Chinese Research Council.en_GB
dc.identifier.citationPublished online 26 October 2017en_GB
dc.identifier.doi10.1109/ACCESS.2017.2766923
dc.identifier.urihttp://hdl.handle.net/10871/30119
dc.language.isoenen_GB
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en_GB
dc.rightsOpen access. This work is licensed under a Creative Commons Attribution 3.0 License. For more information, see http://creativecommons.org/licenses/by/3.0/.en_GB
dc.subjectCloud computingen_GB
dc.subjectComputer architectureen_GB
dc.subjectEdge computingen_GB
dc.subjectOptimizationen_GB
dc.subjectLogic gatesen_GB
dc.subjectBig Dataen_GB
dc.subjectFog computingen_GB
dc.subjectGenetic Algorithmsen_GB
dc.subjectInternet of Thingsen_GB
dc.titleA Framework of Fog Computing: Architecture, Challenges and Optimizationen_GB
dc.typeArticleen_GB
dc.date.available2017-11-02T14:05:52Z
dc.descriptionThis is the author accepted manuscript. The final version is available from IEEE via the DOI in this record.en_GB
dc.identifier.journalIEEE Accessen_GB


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