Group : Parallel Systems

Asynchronous Self-stabilizing Stable Marriage

Starts on 01/10/2015
Advisor : BEAUQUIER, Joffroy

Funding :
Affiliation : vide
Laboratory : LRI, salle des thèses

Defended on 30/09/2020, committee :

Research activities :

Abstract :
The Stable Marriage Problem (SMP) is a matching problem where participants have preferences over their potential partners. The objective is to find a matching that is optimal (stable in certain sens) with regard to these preferences. This type of matching has a lot of widely used applications such as the assignment of children to schools, interns to hospitals, kidney transplant patients to donors, as well as taxi scheduling or content delivery on the Internet. Some applications can be solved in a centralized way while others, due to their distributed nature and their complex data, need a different treatment.

In order to handle this challenge, we provide two distributed self-stabilizing solutions (i.e., that tolerate transient (or short-lived) failures (e.g., memory or message corruptions) of any nodes. The privacy of the preference lists is guaranteed by the two proposed algorithms: lists are not shared, only some binary queries and responses are transmitted.
For both algorithms, executions proceed in atomic steps and a daemon (distributed unfair daemon) conveys the notion of asynchrony. Under this daemon, the stabilization time can be bounded in term of moves (local computations). This complexity metrics allows to evaluate the necessary computational power or the energy consumption of the algorithm's executions.

The first algorithm, based on the centralized method of Ackermann et al. (SICOMP' 2011), solves the problem in O(n^4) moves.

The starting point of the second algorithm is the local detection/global correction scheme of Awerbuch et al. (DA' 1994)
Unfortunately, local checkability definition of DA '1994 does not apply to our case (in particular due to the unfair daemon).
Consequently, we propose a new definition.
Furthermore, we design a distributed self-stabilizing asynchronous reset algorithm.
Using it, the resulting composed algorithm solves SMP in Theta(n^2) moves in a self-stabilizing way.

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.