Advancing IoT Platforms Interoperability

The IoT European Platforms Initiative (IoT-EPI) projects are addressing the topic of Internet of Things and Platforms for Connected Smart Objects and aim to deliver an IoT extended into a web of platforms for connected devices and objects that supports smart environments, businesses, services and persons with dynamic and adaptive configuration capabilities. The specific areas of focus of the research activities are architectures and semantic interoperability, which reliably cover multiple use cases. The goal is to deliver dynamically-configured infrastructure and integration platforms for connected smart objects covering multiple technologies and multiple intelligent artefacts. The IoT-EPI ecosystem has been created with the objective of increasing the impact of the IoT-related European research and innovation, including seven European promising projects on IoT platforms: AGILE, BIG IoT, INTER-IoT, VICINITY, SymbIoTe, bIoTope, and TagItSmart.This white paper provides an insight regarding interoperability in the IoT platforms and ecosystems created and used by IoT-EPI. The scope of this document covers the interoperability aspects, challenges and approaches that cope with interoperability in the current existing IoT platforms and presents some insights regarding the future of interoperability in this context. It presents possible solutions, and a possible IoT interoperability platform architecture

Internet of Things backend for embedded systems teaching

Abstract. In this work, the Internet of Things system is implemented for enabling distance learning and laboratory work for an embedded systems programming course at the University of Oulu. The system must meet the following three requirements. The system receives and visualizes sensor data from the embedded device. The system enables two-way communication with the cloud application and the embedded device. The system can be connected via the public Internet, where the system is managed through Kubernetes. The architecture of the system is described in three different layers. The perception layer contains embedded devices used to produce sensor data. The components of the network layer process and transmit data. The cloud layer includes data storage and further processing in the application, as well as data visualization. The architecture of the implemented system consists of distributed microservices that are deployed using container technology. The system was tested on the basis of feedback collected from the beta version implemented in autumn 2020, as well as use cases defined by the developers, which were constructed from previously known problem areas. As a result, modular and scalable future distance learning system for embedded systems was developed.Tiivistelmä. Tässä työssä suunnitellaan ja toteutetaan etäopiskelun sekä -laboratoriotyön mahdollistava esineiden internetin järjestelmä sulautettujen järjestelmien ohjelmoinnin kurssille Oulun yliopistossa. Järjestelmän tulee toteuttaa seuraavat kolme vaatimusta. Järjestelmä vastaanottaa ja visualisoi anturitietoa sulautetulta laitteelta. Järjestelmä mahdollistaa kaksisuuntaisen viestinnän pilvisovelluksen ja sulautetun laitteen kanssa. Järjestelmään saa yhteyden julkisen Internetin kautta, jossa järjestelmään hallinnoidaan Kubernetesin avulla. Järjestelmän arkkitehtuuri kuvataan kolmena eri kerroksena. Havaintokerros sisältää sulautettuja laitteita, joita käytetään anturitiedon tuottamiseen. Verkkokerroksen komponentit käsittelevät ja välittävät dataa. Pilvikerros sisältää tietojen tallennuksen ja jatkokäsittelyn sovelluksessa, sekä tietojen visualisoinnin. Toteutetun järjestelmän arkkitehtuuri koostuu hajautetuista mikropalveluista, jotka otetaan käyttöön konttiteknologian avulla. Järjestelmää testattiin perustuen syksyllä 2020 toteutetusta kokeiluversiosta kerättyyn palautteeseen sekä kehittäjien määrittelemiin käyttötapauksiin, jotka luotiin hyödyntäen entuudestaan tunnettuja ongelma-alueita. Työn tuloksena valmistui modulaarinen ja skaalautuva tulevaisuuden etäopetusjärjestelmä sulautettujen järjestelmien ohjelmoinnin kursseille

Distributed Computing Framework Based on Software Containers for Heterogeneous Embedded Devices

The Internet of Things (IoT) is represented by millions of everyday objects enhanced with sensing and actuation capabilities that are connected to the Internet. Traditional approaches for IoT applications involve sending data to cloud servers for processing and storage, and then relaying commands back to devices. However, this approach is no longer feasible due to the rapid growth of IoT in the network: the vast amount of devices causes congestion; latency and security requirements demand that data is processed close to the devices that produce and consume it; and the processing and storage resources of devices remain underutilized. Fog Computing has emerged as a new paradigm where multiple end-devices form a shared pool of resources where distributed applications are deployed, taking advantage of local capabilities. These devices are highly heterogeneous, with varying hardware and software platforms. They are also resource-constrained, with limited availability of processing and storage resources. Realizing the Fog requires a software framework that simplifies the deployment of distributed applications, while at the same time overcoming these constraints. In Cloud-based deployments, software containers provide a lightweight solution to simplify the deployment of distributed applications. However, Cloud hardware is mostly homogeneous and abundant in resources. This work establishes the feasibility of using Docker Swarm -- an existing container-based software framework -- for the deployment of distributed applications on IoT devices. This is realized with the use of custom tools to enable minimal-size applications compatible with heterogeneous devices; automatic configuration and formation of device Fog; remote management and provisioning of devices. The proposed framework has significant advantages over the state of the art, namely, it supports Fog-based distributed applications, it overcomes device heterogeneity and it simplifies device initialization