EiF: Toward an Elastic IoT Fog Framework for AI Services

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dc.contributor Aalto-yliopisto fi
dc.contributor Aalto University en
dc.contributor.author An, Jonggwan
dc.contributor.author Li, Wenbin
dc.contributor.author Gall, Franck Le
dc.contributor.author Kovac, Ernoe
dc.contributor.author Kim, Jaeho
dc.contributor.author Taleb, Tarik
dc.contributor.author Song, Jaeseung
dc.date.accessioned 2019-08-15T08:28:17Z
dc.date.available 2019-08-15T08:28:17Z
dc.date.issued 2019-05-01
dc.identifier.citation An , J , Li , W , Gall , F L , Kovac , E , Kim , J , Taleb , T & Song , J 2019 , ' EiF: Toward an Elastic IoT Fog Framework for AI Services ' IEEE Communications Magazine , vol. 57 , no. 5 , 8713796 , pp. 28-33 . https://doi.org/10.1109/MCOM.2019.1800215 en
dc.identifier.issn 0163-6804
dc.identifier.issn 1558-1896
dc.identifier.other PURE UUID: edbbe54d-1def-4b92-b23a-68f92578c81c
dc.identifier.other PURE ITEMURL: https://research.aalto.fi/en/publications/eif-toward-an-elastic-iot-fog-framework-for-ai-services(edbbe54d-1def-4b92-b23a-68f92578c81c).html
dc.identifier.other PURE LINK: http://www.scopus.com/inward/record.url?scp=85065876772&partnerID=8YFLogxK
dc.identifier.other PURE FILEURL: https://research.aalto.fi/files/35823051/ELEC_An_EiF_Toward_IEEEComm.pdf
dc.identifier.uri https://aaltodoc.aalto.fi/handle/123456789/39769
dc.description.abstract The first generation of IoT was developed and deployed all over the world by connecting devices with common functionalities that were not sufficiently efficient or reliable for use in dynamic situations that require adaptive solutions. However, these fundamental IoT functions and services mainly targeted stable environments; there is consequently a strong need for the next generation of IoT services to be smarter, faster, and more reliable. We believe that the hyper-connected IoT ecosystem on fog platforms with contextual AI technologies is a promising solution. In this work, we introduce the EiF, a flexible fog computing framework that runs on IoT gateways with adaptive AI services fostered on the cloud. Our approach can be viewed as an integration of three emerging technologies, namely IoT, fog, and AI. Generally, EiF virtualizes an IoT service layer platform for fog nodes, and provides functions to manage and orchestrate various fog nodes; upon service virtualization and orchestration, AI services are fostered within both the federated cloud and distributed edge side and are deployed on fog nodes. We demonstrate the feasibility of EiF via the example of intelligent traffic flow monitoring and management. en
dc.format.extent 6
dc.format.extent 28-33
dc.format.mimetype application/pdf
dc.language.iso en en
dc.publisher IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
dc.relation.ispartofseries IEEE Communications Magazine en
dc.relation.ispartofseries Volume 57, issue 5 en
dc.rights openAccess en
dc.subject.other Computer Science Applications en
dc.subject.other Computer Networks and Communications en
dc.subject.other Electrical and Electronic Engineering en
dc.subject.other 213 Electronic, automation and communications engineering, electronics en
dc.subject.other 113 Computer and information sciences en
dc.title EiF: Toward an Elastic IoT Fog Framework for AI Services en
dc.type A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä fi
dc.description.version Peer reviewed en
dc.contributor.department Sejong University
dc.contributor.department Easy Global Market
dc.contributor.department NEC Europe Ltd.
dc.contributor.department Korea Electronics Technologies Institute
dc.contributor.department Mobile Network Softwarization and Service Customization
dc.contributor.department Department of Communications and Networking en
dc.subject.keyword Computer Science Applications
dc.subject.keyword Computer Networks and Communications
dc.subject.keyword Electrical and Electronic Engineering
dc.subject.keyword 213 Electronic, automation and communications engineering, electronics
dc.subject.keyword 113 Computer and information sciences
dc.identifier.urn URN:NBN:fi:aalto-201908154814
dc.identifier.doi 10.1109/MCOM.2019.1800215
dc.type.version acceptedVersion


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