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)
Journal or Series Name: 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.
ISBN: 978-303024921-2
ISSN: 0302-9743
Institute: Telematik E-17 
Type: InProceedings (Aufsatz / Paper einer Konferenz etc.)
Appears in Collections:Publications without fulltext

Show full item record

Page view(s)

checked on Aug 25, 2019

Google ScholarTM



Items in TORE are protected by copyright, with all rights reserved, unless otherwise indicated.