Networking-Aware IoT Application Development.

IoT SDN semantic models

Journal

Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366

Informations de publication

Date de publication:
07 Feb 2020
Historique:
received: 29 11 2019
revised: 29 01 2020
accepted: 31 01 2020
entrez: 13 2 2020
pubmed: 13 2 2020
medline: 13 2 2020
Statut: epublish

Résumé

Various tools support developers in the creation of IoT applications. In general, such tools focus on the business logic, which is important for application development, however, for IoT applications in particular, it is crucial to consider the network, as they are intrinsically based on interconnected devices and services. IoT application developers do not have in depth expertise in configuring networks and physical connections between devices. Hence, approaches are required that automatically deduct these configurations. We address this challenge in this work with an architecture and associated data models that enable networking-aware IoT application development. We evaluate our approach in the context of an application for oil leakage detection in wind turbines.

Identifiants

pubmed: 32046175
pii: s20030897
doi: 10.3390/s20030897
pmc: PMC7038961
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : European Commission
ID : 780315

Auteurs

Arne Bröring (A)

Siemens AG, Corporate Technology, 81739 Munich, Germany.

Jan Seeger (J)

Chair of Networking Architectures and Services, Technical University Munich, 80333 Munich, Germany.

Manos Papoutsakis (M)

School of Mathematics, Computer Sciences and Engineering, City University of London, Northampton Square, London EC1V 0HB, UK.
Foundation for Research and Technology Hellas, Institute of Computer Science; N.Plastira 100, 70013 Heraklion, Crete, Greece.

Konstantinos Fysarakis (K)

Sphynx Technology Solutions AG, 6300 Zug, Switzerland.

Ahmad Caracalli (A)

EURECOM, Campus SophiaTech, 06410 Biot, France.

Classifications MeSH