Publisher DOI: 10.1007/978-3-030-24922-9_21
Title: Making randomized algorithms self-stabilizing
Language: English
Authors: Turau, Volker 
Issue Date: Jul-2019
Source: Lecture Notes in Computer Science (11639 LNCS): 309-324 (2019-06)
Part of Series: Lecture notes in computer science 
Abstract (english): It is well known that the areas of self-stabilizing algorithms and local algorithms are closely related. Using program transformation techniques local algorithms can be made self-stabilizing, albeit an increase in run-time or memory consumption is often unavoidable. Unfortunately these techniques often do not apply to randomized algorithms, which are often simpler and faster than deterministic algorithms. In this paper we demonstrate that it is possible to take over ideas from randomized distributed algorithms to self-stabilizing algorithms. We present two simple self-stabilizing algorithms computing a maximal independent set and a maximal matching and terminate in the synchronous model with high probability in O(log n) rounds. The algorithms outperform all existing algorithms that do not rely on unique identifiers.
Conference: 26th International Colloquium on Structural Information and Communication Complexity SIROCCO 2019 
ISBN: 978-303024921-2
Institute: Telematik E-17 
Type: InProceedings (Aufsatz / Paper einer Konferenz etc.)
Project: Tolerance-Zone - Fehlertolerante Middleware-Idiome basierend auf selbststabilisierenden Techniken 
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