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Efficient self-stabilizing algorithms for graphs

Abstract : The main focus of my thesis is the design of an efficient kind of distributed algorithms, known as: Self-stabilizing. These algorithms have the property to recover from faults in the environment they're executed in, and this without any human intervention. Recovering here, means converging toward a pre-defined, correct configuration. In this setting, I was mainly interested by the problems of matching in graphs, clique partitions and publication subscription paradigms. For the maximal version of the matching problem in anonymous graphs, we achieved a more efficient randomized, self-stabilizing algorithm. This work is published in a journal version in PPL. The maximum version of the same problem, but in an identified setting, led to the design of an efficient self-stabilizing algorithm that approximates the optimal solution up to the 2/3. This result was published at OPODIS. During a research visit at TUHH, Hamburg, Germany. Together with Pr. Volker Turau we tackled the problem of self-stabilizing publish/subscribe paradigms. This led to an algorithm introducing the new notion of short-cuts in this type of structures and was published under a brief announcement and a regular paper at SSS and NetSyS. In collaboration with Mr. Siegemund, then a visiting researcher at LIX, École Polytechnique, we worked on an efficient self-stabilizing algorithm for clique partitions. This work is still in progress and in preparation for an eventual publication.
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https://tel.archives-ouvertes.fr/tel-01630028
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Submitted on : Tuesday, November 7, 2017 - 10:27:33 AM
Last modification on : Friday, October 9, 2020 - 9:51:56 AM
Long-term archiving on: : Thursday, February 8, 2018 - 12:33:40 PM

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Khaled Maamra. Efficient self-stabilizing algorithms for graphs. Data Structures and Algorithms [cs.DS]. Université Paris-Saclay, 2017. English. ⟨NNT : 2017SACLV065⟩. ⟨tel-01630028⟩

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