On the road to the weakest failure detector for k -set agreement in message-passing systems

In the k -set agreement problem, each process (in a set of n processes) proposes a value and has to decide a proposed value in such a way that at most k different values are decided. While this problem can easily be solved in asynchronous systems prone to t process crashes when k > t , it cannot...

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Published inTheoretical computer science Vol. 412; no. 33; pp. 4273 - 4284
Main Authors Bonnet, François, Raynal, Michel
Format Journal Article Conference Proceeding
LanguageEnglish
Published Oxford Elsevier B.V 29.07.2011
Elsevier
Subjects
Online AccessGet full text
ISSN0304-3975
1879-2294
DOI10.1016/j.tcs.2010.11.007

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Abstract In the k -set agreement problem, each process (in a set of n processes) proposes a value and has to decide a proposed value in such a way that at most k different values are decided. While this problem can easily be solved in asynchronous systems prone to t process crashes when k > t , it cannot be solved when k ≤ t . For several years, the failure-detector-based approach has been investigated to circumvent this impossibility. While the weakest failure detector class to solve the k -set agreement problem in read/write shared memory systems has recently been discovered (PODC 2009), the situation is different in message-passing systems where the weakest failure detector classes are known only for the extreme cases k = 1 (consensus) and k = n − 1 (set agreement). This paper presents four contributions whose aim is to help pave the way to discover the weakest failure detector class for k -set agreement in message-passing systems. These contributions are the following. (a) The first is a new failure detector class, denoted Π k , that is such that Π 1 = Σ × Ω (the weakest class for k = 1 ), and Π n − 1 = L (the weakest class for k = n − 1 ). (b) The second is an investigation of the structure of Π k that shows that Π k is the combination of two failure detector classes Σ k (that is new) and Ω k (they generalize the previous “quorums” and “eventual leaders” failure detector classes, respectively). (c) The third contribution concerns Σ k that is shown to be a necessary requirement (as far as information on failure is concerned) to solve the k -set agreement problem in message-passing systems. (d) Finally, the last contribution is a Π n − 1 -based algorithm that solves the ( n − 1 ) -set agreement problem. This algorithm provides us with a new algorithmic insight on the way the ( n − 1 ) -set agreement problem can be solved in asynchronous message-passing systems. It is hoped that these contributions will help discover the weakest failure detector class for k -set agreement in message-passing systems.
AbstractList In the k -set agreement problem, each process (in a set of n processes) proposes a value and has to decide a proposed value in such a way that at most k different values are decided. While this problem can easily be solved in asynchronous systems prone to t process crashes when k > t , it cannot be solved when k less than or equal to t . For several years, the failure-detector-based approach has been investigated to circumvent this impossibility. While the weakest failure detector class to solve the k -set agreement problem in read/write shared memory systems has recently been discovered (PODC 2009), the situation is different in message-passing systems where the weakest failure detector classes are known only for the extreme cases k = 1 (consensus) and k = n - 1 (set agreement). This paper presents four contributions whose aim is to help pave the way to discover the weakest failure detector class for k -set agreement in message-passing systems. These contributions are the following. (a) The first is a new failure detector class, denoted capital pi k , that is such that capital pi 1 = capital sigma Omega (the weakest class for k = 1 ), and capital pi n - 1 = L (the weakest class for k = n - 1 ). (b) The second is an investigation of the structure of capital pi k that shows that capital pi k is the combination of two failure detector classes capital sigma k (that is new) and Omega k (they generalize the previous "quorums" and "eventual leaders" failure detector classes, respectively). (c) The third contribution concerns capital sigma k that is shown to be a necessary requirement (as far as information on failure is concerned) to solve the k -set agreement problem in message-passing systems. (d) Finally, the last contribution is a capital pi n - 1 -based algorithm that solves the ( n - 1 ) -set agreement problem. This algorithm provides us with a new algorithmic insight on the way the ( n - 1 ) -set agreement problem can be solved in asynchronous message-passing systems. It is hoped that these contributions will help discover the weakest failure detector class for k -set agreement in message-passing systems.
In the k -set agreement problem, each process (in a set of n processes) proposes a value and has to decide a proposed value in such a way that at most k different values are decided. While this problem can easily be solved in asynchronous systems prone to t process crashes when k > t , it cannot be solved when k ≤ t . For several years, the failure-detector-based approach has been investigated to circumvent this impossibility. While the weakest failure detector class to solve the k -set agreement problem in read/write shared memory systems has recently been discovered (PODC 2009), the situation is different in message-passing systems where the weakest failure detector classes are known only for the extreme cases k = 1 (consensus) and k = n − 1 (set agreement). This paper presents four contributions whose aim is to help pave the way to discover the weakest failure detector class for k -set agreement in message-passing systems. These contributions are the following. (a) The first is a new failure detector class, denoted Π k , that is such that Π 1 = Σ × Ω (the weakest class for k = 1 ), and Π n − 1 = L (the weakest class for k = n − 1 ). (b) The second is an investigation of the structure of Π k that shows that Π k is the combination of two failure detector classes Σ k (that is new) and Ω k (they generalize the previous “quorums” and “eventual leaders” failure detector classes, respectively). (c) The third contribution concerns Σ k that is shown to be a necessary requirement (as far as information on failure is concerned) to solve the k -set agreement problem in message-passing systems. (d) Finally, the last contribution is a Π n − 1 -based algorithm that solves the ( n − 1 ) -set agreement problem. This algorithm provides us with a new algorithmic insight on the way the ( n − 1 ) -set agreement problem can be solved in asynchronous message-passing systems. It is hoped that these contributions will help discover the weakest failure detector class for k -set agreement in message-passing systems.
Author Bonnet, François
Raynal, Michel
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Issue 33
Keywords Message-passing systems
Failure detectors
Reduction
Quorums
k -set agreement
Asynchronous systems
Eventual leaders
Wait-freedom
Computer theory
Algorithmics
Algorithm
Failures
Consensus
Message passing
k-set agreement
Shared memory systems
Failure
Language English
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Snippet In the k -set agreement problem, each process (in a set of n processes) proposes a value and has to decide a proposed value in such a way that at most k...
In the k -set agreement problem, each process (in a set of n processes) proposes a value and has to decide a proposed value in such a way that at most k...
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SubjectTerms [formula omitted]-set agreement
Algorithmics. Computability. Computer arithmetics
Algorithms
Applied sciences
Asynchronous systems
Computer Science
Computer science; control theory; systems
Crashes
Detectors
Distributed, Parallel, and Cluster Computing
Eventual leaders
Exact sciences and technology
Failure
Failure detectors
Message-passing systems
Miscellaneous
Quorums
Reduction
Roads
Theoretical computing
Wait-freedom
Title On the road to the weakest failure detector for k -set agreement in message-passing systems
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