Time Sensitive Networks: analysis, testing, scheduling and simulation

Cedrini, Luca (2021) Time Sensitive Networks: analysis, testing, scheduling and simulation. [Laurea magistrale], Università di Bologna, Corso di Studio in Automation engineering / ingegneria dell’automazione [LM-DM270]
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The industrial automation world is an extremely complex framework, where state-of-the-art cutting edge technologies are continuously being replaced in order to achieve the best possible performances. The criterion guiding this change has always been the productivity. This term has, however, a broad meaning and there are many ways to improve the productivity, that go beyond the simplistic products/min ratio. One concept that has been increasingly emerging in the last years is the idea of interoperability: a flexible environment, where products of different and diverse vendors can be easily integrated togheter, would increase the productivity by simplifying the design and installation of any automatic system. Connected to this concept of interoperability is the Industrial Internet of Things (IIoT), which is one of the main sources of the industrial innovation at the moment: the idea of a huge network connecting every computer, sensor or generic device so as to allow seamless data exchange, status updates and information passing. It is in this framework that Time Sensitive Networks are placed: it is a new, work-in-progress set of communication standards whose goal is to provide a common infrastructure where all kinds of important data for an industrial automation environment, namely deterministic and non deterministic data, can flow. This work aims to be an initial step towards the actual implementation of the above-mentioned technology. The focus will therefore be not only on the theoretical aspects, but also on a set of practical tests that have been carried out in order to evaluate the performances, the required hardware and software features, advantages and drawbacks of such an application.

Tipologia del documento
Tesi di laurea (Laurea magistrale)
Autore della tesi
Cedrini, Luca
Relatore della tesi
Correlatore della tesi
Corso di studio
Ordinamento Cds
Parole chiave
Time Sensitive Networks (TSN),Industrial Internet of Things,Indusry 4.0,industrial communication
Data di discussione della Tesi
4 Febbraio 2021

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