Description
Date depot: 1 janvier 1900
Titre: Autonomic Mechanisms for IoT services
Directeur de thèse:
Sébastien TIXEUIL (LIP6)
Domaine scientifique: Sciences et technologies de l'information et de la communication
Thématique CNRS : Systèmes et réseaux
Resumé:
The PhD thesis will contribute to our research project by exploring and proposing new autonomous mechanisms within the three following research axes:
1. Self-modeling of IoT services. The digital assistant manipulates Virtual Objects and Chains of Virtual Objects that are respectively the abstractions of the connected objects in the real world and the abstractions of the way they interact together in IoT services. We already investigated typed attributed graphs [9], but this modeling is static and requires
prior knowledge. We would like to go towards self-modeling of IoT services (a bit like what is done in robotics, see for example [10]), incorporating time aspects (e.g., using automata
[11]) and contextualized information (e.g., by monitoring trac
ows between connected objects, see for example [12]).
2. Self-characterization of IoT services. The digital assistant should be able to autonomously understand' what the IoT services in its scope are and how they are working,
self-building an IoT service catalog. Based on the static modeling of axis 1, we already de ned a rst algorithm that gives a signature for each service instance [patent led and publication under submission]. How to adapt/improve/modify it with dynamic (i.e., including time and spatial dimensions) and contextualized information? Do we need to use clustering [13] or machine learning techniques [14]?
3. Self-adaptive mechanisms for IoT services. The IoT service catalog of axis 2 constitutes the knowledge of the digital assistant, which can be used to help people in the usage of new IoT-based services and IoT service administrators in the deployment of IoT services. A bit like in Autonomic Computing [15], one can apply Arti cial Intelligence
techniques [16] on this knowledge to analyze events and take some decisions, learning from past decisions [14]. Autonomic mechanisms will be then de ned using models of axis 1 and self-characterization mechanisms of axis 2.
Doctorant.e: Ammar Nesrine