Integration of FIWARE and IoT based Named Data Networking (IoT-NDN).

Abstract

IoT systems have taken on an essential role in our life. IoT devices are strongly integrated into several sec-
tors such as Smart Healthcare, Smart Cities, Smart Energy, Smart Industry, etc. and deliver important data.
Designing, building, and implementing IoT systems are significant challenges because of IoT requirements
such as mobility, energy consumption, and limited device memory. To mitigate such challenges, opportunities
to test and evaluate IoT systems early in the first development phases are important to reduce cost and effort.
Different systems have been proposed to aid such development, aiming at different key challenges. One of
these systems is FIWARE, an open source IoT middleware, designed to ease data transportation and big data
tasks. It has been established as an ecosystem technology used for optimizing the development of several
applications and services in IoT. Key feature is the standardized architecture for gathering context information
and managing these contexts in cloud based IoT and big data applications. In this paper, we discuss the inte-
gration of FIWARE software and IoT-NDN. IoT-NDN is an IoT system based on the Named Data Networking
(NDN) communication paradigm. NDN is a communication protocol developed for the Internet and uses hi-
erarchical names instead of IP addresses to deliver data on the Internet. IoT-NDN is an advanced architecture
of NDN, conceding the requirements and limitations of IoT devices. In this paper we present an approach
and architecture to integrate FIWARE and IoT-NDN. This integration eases implementation of IoT-NDN in
existing applications, since a transparent compatibility between both systems can be achieved.
Original languageEnglish
Title of host publicationProceedings of the 10th International Conference on Sensor Networks (IPSN)
Number of pages7
Publication date14.02.2022
Pages184-190
DOIs
Publication statusPublished - 14.02.2022

Research Areas and Centers

  • Centers: Center for Artificial Intelligence Luebeck (ZKIL)
  • Research Area: Intelligent Systems

DFG Research Classification Scheme

  • 409-04 Operating, Communication, Database and Distributed Systems

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