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dc.contributor.authorMann, Zoltán Ádám
dc.contributor.authorMetzger, Andreas
dc.contributor.authorPrade, Johannes
dc.contributor.authorSeidl, Robert
dc.contributor.editorFelderer, Michael
dc.contributor.editorHasselbring, Wilhelm
dc.contributor.editorRabiser, Rick
dc.contributor.editorJung, Reiner
dc.date.accessioned2020-02-03T13:03:32Z
dc.date.available2020-02-03T13:03:32Z
dc.date.issued2020
dc.identifier.isbn978-3-88579-694-7
dc.identifier.issn1617-5468
dc.identifier.urihttp://dl.gi.de/handle/20.500.12116/31713
dc.description.abstractFog computing uses geographically distributed fog nodes that can supply nearby end devices with low-latency access to cloud-like compute resources. If the load of a fog node exceeds its capacity, some non-latency-critical application components may be offloaded to the cloud. Using commercial cloud offerings for such offloading incurs financial costs. Optimally deciding which application components to keep in the fog node and which ones to offload to the cloud is a difficult combinatorial problem. We introduce an optimization algorithm that (i) guarantees that the deployment always satisfies capacity constraints and affinity requirements, (ii) achieves near-optimal cloud usage costs, and (iii) is fast enough to be run online. The practical use of the algorithm is illustrated by applying it to optimizing the applications in a mobile factory.en
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofSoftware Engineering 2020
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-300
dc.subjectFog Computing
dc.subjectCost-optimized Software Deployment
dc.subjectResource Optimization
dc.titleOptimized Application Deployment using Fog and Cloud Computing Environmentsen
dc.typeText/Conference Paper
dc.pubPlaceBonn
mci.reference.pages117--119
mci.conference.sessiontitleCloud, Edge und Microservices
mci.conference.locationInnsbruck, Austria
mci.conference.date24.-28. Feburar 2020
dc.identifier.doi10.18420/SE2020_35


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