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Converging on Industrial Deterministic Network

Equipe et encadrants
Département / Equipe: 
Site Web Equipe: 
Directeur de thèse
Nicolas Montavont
Co-directeur(s), co-encadrant(s)
Georgios Papadopoulos
Sujet de thèse

During the last years we experience the emergence of a new paradigm called Internet of Thing (IoT) in which smart, uniquely identifiable and connected objects (e.g., machines, sensors, actuators, or any other devices) construct a network of things. Those things can communicate between themselves or across existing network infrastructure such as the Internet. They can be deployed nearly everywhere, at homes, hospitals, cities, agricultural fields, even at human bodies.

While we name this the Internet of Things, different applications require different network performance. A given network of objects must be carefully designed for its target application. Bandwidth, loss, delay and jitter must be managed more or less accurately depending on the application requirements. Among these applications, the Industry 4.0 is an emerging concept. 

To reduce the operational, automation, management and production cost and to simplify the production chain, the IoT technology is now considered in the industrial domain, also called the Industry 4.0. The Industry 4.0 ambition is to make the factory more flexible and adaptable. The main goal is to replace the existing cables with a wireless medium, while guaranteeing network reliability above 99.999%. Furthermore, the Industry 4.0 requires robust communications, messages need to be sent securely and the communication framework must guarantee message delivery in a given delay with jitter close to 0. In addition, some environments may require a dense network, with thousand of nodes sending a large amount of messages. Scalability is thus another constraint imposed by the Industry 4.0. To reach this ambition, the wireless industrial network must be not only reliable, but also deterministic and predictable. 

The main scope of the PhD student will be to focus on investigating and designing techniques on improving the deterministic solutions (i.e., algorithms to reduce the latency, jitter while achieving 100% of network reliability), by considering the predefined constraints from the Industry 4.0 application layer. In the first months of the thesis, the PhD student will prepare a state of the art on the Internet of Things, particularly the Quality of Service techniques that are available in the literature. In parallel, he/she will study the Industry 4.0 context and requirements, and prepare a clear problem statement and requirements. 

Then, different research will be conducted to propose original and innovative approach to provide service differentiation and quality of service in Industrial IoT. Hybrid technologies, opportunistic routing, mobility support, deterministic delivery, link quality assessment will be thoroughly investigated.

This work will be strengthened with experimentation over real world devices and conditions, such as the open FIT IoT-LAB platform (located in 7 sites in France), Smart Grid testbed (located in Rennes) to evaluate the proposed solutions under real-world conditions. A thorough measurement campaign will be conducted to evaluate the robustness, efficiency, and even more importantly, the repeatability and the reproducibility. 


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Début des travaux: 
Mots clés: 
Internet of Things, Deterministm, Industry 4.0, Multi-path Routing Algorithm, Route Diversity, IEEE802.15.4-2015
IRISA - IMT Atlantique, Rennes