Ph.D
Group : Parallelism

Observing self-stabilization

Starts on 09/01/2002
Advisor : ROZOY, Brigitte
[Joffroy BEAUQUIER]

Funding : MNRT
Affiliation : Université Paris-Saclay
Laboratory : LRI

Defended on 15/12/2005, committee :

Research activities :
   - Verification
   - Distributed algorithms
   - Self-stabilisation
   - Design
   - Fault Tolerance

Abstract :
Distributed systems have two main characteristics: they are complex
and subject to failures. So, the verification and the study of fault
tolerance in such systems are two major issues. In this thesis, we
propose a model-checking verification technique for
distributed systems. We present and prove an algorithm, based on
partial orders, which builds a small subset of the whole set of states
of a distributed system. In the reduced generated graph, it is still
possible to verify stable properties of the considered system. We
then study self-stabilizing systems which are fault tolerant
distributed systems. Self-stabilizing systems are systems which, from
any initialization, eventually behaves correctly, regarding to their
specifications. The drawback of such systems is that they cannot
determine whether or not they verify their specifications. In this
thesis we propose a new model, in which the system can decide if it
verifies its specification by introducing a new abstraction called
observer. With this model, we prove that if there exists a synchronous
self-stabilizing distributed solution for some problem in a
distinguished network, then there exists a synchronous
self-stabilizing distributed solution for the same problem in the same
network which accepts an observer. Finally, we introduce the notion of
a probabilistic observer and we prove that such an observer allows to
decide for a larger class of self-stabilizing systems than
deterministic observers.

More information: http://info.iut-bm.univ-fcomte.fr/staff/pilard/publication/publication.php

CAUSAL LEARNING FOR DIAGNOSTIC SUPPORT


CAUSAL UNCERTAINTY QUANTIFICATION UNDER PARTIAL KNOWLEDGE AND LOW DATA REGIMES


MICRO VISUALIZATIONS: DESIGN AND ANALYSIS OF VISUALIZATIONS FOR SMALL DISPLAY SPACES
The topic of this habilitation is the study of very small data visualizations, micro visualizations, in display contexts that can only dedicate minimal rendering space for data representations. For several years, together with my collaborators, I have been studying human perception, interaction, and analysis with micro visualizations in multiple contexts. In this document I bring together three of my research streams related to micro visualizations: data glyphs, where my joint research focused on studying the perception of small-multiple micro visualizations, word-scale visualizations, where my joint research focused on small visualizations embedded in text-documents, and small mobile data visualizations for smartwatches or fitness trackers. I consider these types of small visualizations together under the umbrella term ``micro visualizations.'' Micro visualizations are useful in multiple visualization contexts and I have been working towards a better understanding of the complexities involved in designing and using micro visualizations. Here, I define the term micro visualization, summarize my own and other past research and design guidelines and outline several design spaces for different types of micro visualizations based on some of the work I was involved in since my PhD.