Analysing Randomized Distributed Algorithms
Identifieur interne : 002216 ( Istex/Corpus ); précédent : 002215; suivant : 002217Analysing Randomized Distributed Algorithms
Auteurs : Gethin NormanSource :
- Lecture Notes in Computer Science [ 0302-9743 ] ; 2004.
Abstract
Abstract: Randomization is of paramount importance in practical applications and randomized algorithms are used widely, for example in co-ordinating distributed computer networks, message routing and cache management. The appeal of randomized algorithms is their simplicity and elegance. However, this comes at a cost: the analysis of such systems become very complex, particularly in the context of distributed computation. This arises through the interplay between probability and nondeterminism. To prove a randomized distributed algorithm correct one usually involves two levels: classical, assertion-based reasoning, and a probabilistic analysis based on a suitable probability space on computations. In this paper we describe a number of approaches which allows us to verify the correctness of randomized distributed algorithms.
Url:
DOI: 10.1007/978-3-540-24611-4_11
Links to Exploration step
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<front><div type="abstract" xml:lang="en">Abstract: Randomization is of paramount importance in practical applications and randomized algorithms are used widely, for example in co-ordinating distributed computer networks, message routing and cache management. The appeal of randomized algorithms is their simplicity and elegance. However, this comes at a cost: the analysis of such systems become very complex, particularly in the context of distributed computation. This arises through the interplay between probability and nondeterminism. To prove a randomized distributed algorithm correct one usually involves two levels: classical, assertion-based reasoning, and a probabilistic analysis based on a suitable probability space on computations. In this paper we describe a number of approaches which allows us to verify the correctness of randomized distributed algorithms.</div>
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<ChapterHeader><AuthorGroup><Author AffiliationIDS="Aff9"><AuthorName DisplayOrder="Western"><GivenName>Gethin</GivenName>
<FamilyName>Norman</FamilyName>
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<Contact><Email>G.Norman@cs.bham.ac.uk</Email>
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<Affiliation ID="Aff9"><OrgDivision>School of Computer Science</OrgDivision>
<OrgName>University of Birmingham</OrgName>
<OrgAddress><City>Birmingham</City>
<Postcode>B15 2TT</Postcode>
<Country>United Kingdom</Country>
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<Abstract ID="Abs1" Language="En"><Heading>Abstract</Heading>
<Para>Randomization is of paramount importance in practical applications and randomized algorithms are used widely, for example in co-ordinating distributed computer networks, message routing and cache management. The appeal of randomized algorithms is their simplicity and elegance. However, this comes at a cost: the analysis of such systems become very complex, particularly in the context of distributed computation. This arises through the interplay between probability and nondeterminism. To prove a randomized distributed algorithm correct one usually involves two levels: classical, assertion-based reasoning, and a probabilistic analysis based on a suitable probability space on computations. In this paper we describe a number of approaches which allows us to verify the correctness of randomized distributed algorithms.</Para>
</Abstract>
<ArticleNote Type="Misc"><SimplePara>Supported in part by the EPSRC grant GR/N22960.</SimplePara>
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<mods version="3.6"><titleInfo lang="en"><title>Analysing Randomized Distributed Algorithms</title>
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<name type="personal"><namePart type="given">Gethin</namePart>
<namePart type="family">Norman</namePart>
<affiliation>School of Computer Science, University of Birmingham, B15 2TT, Birmingham, United Kingdom</affiliation>
<affiliation>E-mail: G.Norman@cs.bham.ac.uk</affiliation>
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<abstract lang="en">Abstract: Randomization is of paramount importance in practical applications and randomized algorithms are used widely, for example in co-ordinating distributed computer networks, message routing and cache management. The appeal of randomized algorithms is their simplicity and elegance. However, this comes at a cost: the analysis of such systems become very complex, particularly in the context of distributed computation. This arises through the interplay between probability and nondeterminism. To prove a randomized distributed algorithm correct one usually involves two levels: classical, assertion-based reasoning, and a probabilistic analysis based on a suitable probability space on computations. In this paper we describe a number of approaches which allows us to verify the correctness of randomized distributed algorithms.</abstract>
<relatedItem type="host"><titleInfo><title>Validation of Stochastic Systems</title>
<subTitle>A Guide to Current Research</subTitle>
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<name type="personal"><namePart type="given">Christel</namePart>
<namePart type="family">Baier</namePart>
<affiliation>Institute for Theoretical Computer Science, Technical University Dresden, Germany</affiliation>
<affiliation>E-mail: baier@tcs.inf.tu-dresden.de</affiliation>
<role><roleTerm type="text">editor</roleTerm>
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</name>
<name type="personal"><namePart type="given">Boudewijn</namePart>
<namePart type="given">R.</namePart>
<namePart type="family">Haverkort</namePart>
<affiliation>Centre for Telematics and Information Technology, Faculty for Electrical Engineering, Mathematics and Computer Science, University of Twente, P.O. Box 217, 7500, AE, Netherlands</affiliation>
<affiliation>E-mail: b.r.h.m.haverkort@utwente.nl</affiliation>
<role><roleTerm type="text">editor</roleTerm>
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<name type="personal"><namePart type="given">Holger</namePart>
<namePart type="family">Hermanns</namePart>
<affiliation>VASY, INRIA, Grenoble Rhône-Alpes, France</affiliation>
<affiliation>E-mail: hermanns@cs.uni-sb.de</affiliation>
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<name type="personal"><namePart type="given">Joost-Pieter</namePart>
<namePart type="family">Katoen</namePart>
<affiliation>Software Modeling and Verification, RWTH Aachen University, Germany</affiliation>
<affiliation>E-mail: katoen@cs.rwth-aachen.de</affiliation>
<role><roleTerm type="text">editor</roleTerm>
</role>
</name>
<name type="personal"><namePart type="given">Markus</namePart>
<namePart type="family">Siegle</namePart>
<affiliation>Institut für Technische Informatik, Universität der Bundeswehr München</affiliation>
<affiliation>E-mail: markus.siegle@unibw.de</affiliation>
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<topic authority="SpringerSubjectCodes" authorityURI="I16013">Computation by Abstract Devices</topic>
<topic authority="SpringerSubjectCodes" authorityURI="I1603X">Logics and Meanings of Programs</topic>
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<topic authority="SpringerSubjectCodes" authorityURI="I13014">Processor Architectures</topic>
<topic authority="SpringerSubjectCodes" authorityURI="I21025">Simulation and Modeling</topic>
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<identifier type="DOI">10.1007/b98484</identifier>
<identifier type="ISBN">978-3-540-22265-1</identifier>
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<identifier type="ISSN">0302-9743</identifier>
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<identifier type="BookTitleID">83139</identifier>
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<part><date>2004</date>
<detail type="part"><title>Deductive Verification of Stochastic Systems</title>
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<detail type="volume"><number>2925</number>
<caption>vol.</caption>
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<extent unit="pages"><start>384</start>
<end>418</end>
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<relatedItem type="series"><titleInfo><title>Lecture Notes in Computer Science</title>
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<name type="personal"><namePart type="given">Gerhard</namePart>
<namePart type="family">Goos</namePart>
<affiliation>Karlsruhe University, Germany</affiliation>
<role><roleTerm type="text">editor</roleTerm>
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</name>
<name type="personal"><namePart type="given">Juris</namePart>
<namePart type="family">Hartmanis</namePart>
<affiliation>Cornell University, NY, USA</affiliation>
<role><roleTerm type="text">editor</roleTerm>
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<name type="personal"><namePart type="given">Jan</namePart>
<namePart type="family">van Leeuwen</namePart>
<affiliation>Utrecht University, The Netherlands</affiliation>
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