Front-End Intelligence for Large-Scale Application-Oriented Internet-of-Things

Handle URI:
http://hdl.handle.net/10754/614417
Title:
Front-End Intelligence for Large-Scale Application-Oriented Internet-of-Things
Authors:
Bader, Ahmed; Ghazzai, Hakim; Kadri, Abdullah; Alouini, Mohamed-Slim ( 0000-0003-4827-1793 )
Abstract:
The Internet-of-things (IoT) refers to the massive integration of electronic devices, vehicles, buildings, and other objects to collect and exchange data. It is the enabling technology for a plethora of applications touching various aspects of our lives such as healthcare, wearables, surveillance, home automation, smart manufacturing, and intelligent automotive systems. Existing IoT architectures are highly centralized and heavily rely on a back-end core network for all decision-making processes. This may lead to inefficiencies in terms of latency, network traffic management, computational processing, and power consumption. In this paper, we advocate the empowerment of front-end IoT devices to support the back-end network in fulfilling end-user applications requirements mainly by means of improved connectivity and efficient network management. A novel conceptual framework is presented for a new generation of IoT devices that will enable multiple new features for both the IoT administrators as well as end users. Exploiting the recent emergence of software-defined architecture, these smart IoT devices will allow fast, reliable, and intelligent management of diverse IoT-based applications. After highlighting relevant shortcomings of the existing IoT architectures, we outline some key design perspectives to enable front-end intelligence while shedding light on promising future research directions.
KAUST Department:
Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division
Citation:
Front-End Intelligence for Large-Scale Application-Oriented Internet-of-Things 2016:1 IEEE Access
Publisher:
Institute of Electrical and Electronics Engineers (IEEE)
Journal:
IEEE Access
Issue Date:
14-Jun-2016
DOI:
10.1109/ACCESS.2016.2580623
Type:
Article
ISSN:
2169-3536
Sponsors:
The work was made possible by NPRP grant #6-001-2-001 from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors.
Additional Links:
http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=7491206
Appears in Collections:
Articles

Full metadata record

DC FieldValue Language
dc.contributor.authorBader, Ahmeden
dc.contributor.authorGhazzai, Hakimen
dc.contributor.authorKadri, Abdullahen
dc.contributor.authorAlouini, Mohamed-Slimen
dc.date.accessioned2016-06-23T10:59:11Z-
dc.date.available2016-06-23T10:59:11Z-
dc.date.issued2016-06-14-
dc.identifier.citationFront-End Intelligence for Large-Scale Application-Oriented Internet-of-Things 2016:1 IEEE Accessen
dc.identifier.issn2169-3536-
dc.identifier.doi10.1109/ACCESS.2016.2580623-
dc.identifier.urihttp://hdl.handle.net/10754/614417-
dc.description.abstractThe Internet-of-things (IoT) refers to the massive integration of electronic devices, vehicles, buildings, and other objects to collect and exchange data. It is the enabling technology for a plethora of applications touching various aspects of our lives such as healthcare, wearables, surveillance, home automation, smart manufacturing, and intelligent automotive systems. Existing IoT architectures are highly centralized and heavily rely on a back-end core network for all decision-making processes. This may lead to inefficiencies in terms of latency, network traffic management, computational processing, and power consumption. In this paper, we advocate the empowerment of front-end IoT devices to support the back-end network in fulfilling end-user applications requirements mainly by means of improved connectivity and efficient network management. A novel conceptual framework is presented for a new generation of IoT devices that will enable multiple new features for both the IoT administrators as well as end users. Exploiting the recent emergence of software-defined architecture, these smart IoT devices will allow fast, reliable, and intelligent management of diverse IoT-based applications. After highlighting relevant shortcomings of the existing IoT architectures, we outline some key design perspectives to enable front-end intelligence while shedding light on promising future research directions.en
dc.description.sponsorshipThe work was made possible by NPRP grant #6-001-2-001 from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors.en
dc.language.isoenen
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en
dc.relation.urlhttp://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=7491206en
dc.rights(c) 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.en
dc.subjectInternet of things (IoT)en
dc.subjectadministrative domainsen
dc.subjectcollaboration and socializationen
dc.subjectedge computingen
dc.subjectfog computingen
dc.subjectfront-end intelligenceen
dc.subjectsoftware-defined architecturesen
dc.titleFront-End Intelligence for Large-Scale Application-Oriented Internet-of-Thingsen
dc.typeArticleen
dc.contributor.departmentComputer, Electrical and Mathematical Science and Engineering (CEMSE) Divisionen
dc.identifier.journalIEEE Accessen
dc.eprint.versionPost-printen
dc.contributor.institutionQatar Mobility Innovations Center (QMIC), Qatar University, Doha, Qataen
dc.contributor.affiliationKing Abdullah University of Science and Technology (KAUST)en
kaust.authorBader, Ahmeden
kaust.authorAlouini, Mohamed-Slimen
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