Please use this identifier to cite or link to this item: https://hdl.handle.net/11499/46871
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dc.contributor.authorKok, Ibrahim-
dc.contributor.authorOkay, Feyza Yildirim-
dc.contributor.authorOzdemir, Suat-
dc.date.accessioned2023-01-09T21:16:36Z-
dc.date.available2023-01-09T21:16:36Z-
dc.date.issued2022-
dc.identifier.issn2543-1536-
dc.identifier.issn2542-6605-
dc.identifier.urihttps://doi.org/10.1016/j.iot.2022.100572-
dc.identifier.urihttps://hdl.handle.net/11499/46871-
dc.description.abstractIn this paper, we present a novel artificial intelligence-based fog controller, called FogAI that provides a versatile control mechanism to the fog layer. FogAI not only abstracts the control mechanism from the fog environment but also offers potential solutions for the problems of fog-based Next Generation Internet of Things (NGIoT) systems. To this end, we first present a comprehensive examination of challenging issues in Fog Computing (FC). Then, we outline possible FogAI based solutions to these challenges from different perspectives. To illustrate the feasibility of our FogAI concept, we design a use case scenario for task offloading problem in FC. Then, we propose a Deep Q-Learning (DQL) algorithm that autonomously performs task offloading in delay-sensitive and computationally-intensive IoT applications and test it on FogAI. The results show that the proposed FogAI-assisted DQL algorithm is superior to existing offloading policies.en_US
dc.description.sponsorshipScientific and Technological Research Council of Turkey (TUBITAK) [118E212]en_US
dc.description.sponsorshipThis work is supported by The Scientific and Technological Research Council of Turkey (TUBITAK) under the grant number 118E212.en_US
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.relation.ispartofInternet Of Thingsen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectFogAIen_US
dc.subjectFog computingen_US
dc.subjectArtificial intelligenceen_US
dc.subjectDeepQ-learningen_US
dc.subjectTask offloadingen_US
dc.subjectIoTen_US
dc.subjectNGIoTen_US
dc.subjectResource-Allocationen_US
dc.subjectCloud Controlen_US
dc.subjectEdgeen_US
dc.subjectSecurityen_US
dc.subjectInterneten_US
dc.subjectSdnen_US
dc.subjectCommunicationen_US
dc.subjectOptimizationen_US
dc.subjectThingsen_US
dc.subjectReliabilityen_US
dc.titleFogAI: An AI-supported fog controller for Next Generation IoTen_US
dc.typeArticleen_US
dc.identifier.volume19en_US
dc.authoridkök, ibrahim/0000-0001-9787-8079-
dc.authoridOzdemir, Suat/0000-0002-4588-4538-
dc.identifier.doi10.1016/j.iot.2022.100572-
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.authorscopusid57200283688-
dc.authorscopusid55568614900-
dc.authorscopusid23467461900-
dc.authorwosidkök, ibrahim/AAR-2061-2020-
dc.authorwosidOzdemir, Suat/D-8406-2012-
dc.identifier.scopus2-s2.0-85134607327en_US
dc.identifier.wosWOS:000834078100002en_US
item.grantfulltextnone-
item.fulltextNo Fulltext-
item.cerifentitytypePublications-
item.openairetypeArticle-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.languageiso639-1en-
crisitem.author.dept10.10. Computer Engineering-
Appears in Collections:Mühendislik Fakültesi Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
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