The Internet of Things (IoT) leads to an ever-growing presence of ubiquitous networked computing devices in public, business, and private spaces. These devices do not simply act as sensors, but feature computational, storage, and networking resources. Being located at the edge of the network, these resources can be exploited to execute IoT applications in a distributed manner. This concept is known as fog computing. While the theoretical foundations of fog computing are already established, there is a lack of resource provisioning approaches to enable the exploitation of fog-based computational resources. To resolve this shortcoming, we present a conceptual fog computing framework. Then, we model the service placement problem for IoT applications over fog resources as an optimization problem, which explicitly considers the heterogeneity of applications and resources in terms of Quality of Service attributes. Finally, we propose a genetic algorithm as a problem resolution heuristic and show, through experiments, that the service execution can achieve a reduction of network communication delays when the genetic algorithm is used, and a better utilization of fog resources when the exact optimization method is applied.
en
dc.language
English
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dc.language.iso
en
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dc.publisher
Springer
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dc.relation.ispartof
Pharmaceutical Research
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dc.rights.uri
http://creativecommons.org/licenses/by/4.0/
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dc.subject
bioprocess
en
dc.subject
data mining
en
dc.subject
modelling
en
dc.subject
monitoring
en
dc.subject
optimization
en
dc.title
Model-Based Methods in the Biopharmaceutical Process Lifecycle
en
dc.type
Article
en
dc.type
Artikel
de
dc.rights.license
Creative Commons Namensnennung 4.0 International
de
dc.rights.license
Creative Commons Attribution 4.0 International
en
dcterms.dateSubmitted
2017-07-05
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dc.rights.holder
The Author(s) 2017
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dc.type.category
Original Research Article
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tuw.journal.peerreviewed
true
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tuw.peerreviewed
true
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tuw.version
vor
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dcterms.isPartOf.title
Pharmaceutical Research
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tuw.publication.orgunit
E166 - Institut für Verfahrenstechnik, Umwelttechnik und technische Biowissenschaften