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Verification of the Randomized Consensus Algorithm of Aspnes and Herlihy: a Case Study
, 1997
"... The Probabilistic I/O Automaton model of [20] is used as the basis for a formal presentation and proof of the randomized consensus algorithm of Aspnes and Herlihy. The algorithm guarantees termination within expected polynomial time. ..."
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Cited by 50 (10 self)
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The Probabilistic I/O Automaton model of [20] is used as the basis for a formal presentation and proof of the randomized consensus algorithm of Aspnes and Herlihy. The algorithm guarantees termination within expected polynomial time.
Veri cation of the randomized consensus algorithm of Aspnes and Herlihy: a case study
 In WDAG97 Distributed Algorithms 11th International Workshop Proceedings, SpringerVerlag LNCS:1320
, 1997
"... Abstract. The Probabilistic I/O Automaton model of [11] is used as the basis for a formal presentation and proof of the randomized consensus algorithm of Aspnes and Herlihy. The algorithm is highly nontrivial and guarantees termination within expected polynomial time. The task of carrying out this ..."
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Cited by 1 (0 self)
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Abstract. The Probabilistic I/O Automaton model of [11] is used as the basis for a formal presentation and proof of the randomized consensus algorithm of Aspnes and Herlihy. The algorithm is highly nontrivial and guarantees termination within expected polynomial time. The task of carrying out
WaitFree Synchronization
 ACM Transactions on Programming Languages and Systems
, 1993
"... A waitfree implementation of a concurrent data object is one that guarantees that any process can complete any operation in a finite number of steps, regardless of the execution speeds of the other processes. The problem of constructing a waitfree implementation of one data object from another lie ..."
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Cited by 873 (28 self)
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lies at the heart of much recent work in concurrent algorithms, concurrent data structures, and multiprocessor architectures. In the first part of this paper, we introduce a simple and general technique, based on reduction to a consensus protocol, for proving statements of the form "
Quantized consensus
, 2007
"... We study the distributed averaging problem on arbitrary connected graphs, with the additional constraint that the value at each node is an integer. This discretized distributed averaging problem models several problems of interest, such as averaging in a network with finite capacity channels and loa ..."
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Cited by 150 (0 self)
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and load balancing in a processor network. We describe simple randomized distributed algorithms which achieve consensus to the extent that the discrete nature of the problem permits. We give bounds on the convergence time of these algorithms for fully connected networks and linear networks.
Fast Randomized Consensus using Shared Memory
 Journal of Algorithms
, 1988
"... We give a new randomized algorithm for achieving consensus among asynchronous processes that communicate by reading and writing shared registers. The fastest previously known algorithm has exponential expected running time. Our algorithm is polynomial, requiring an expected O(n 4 ) operations ..."
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Cited by 136 (32 self)
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We give a new randomized algorithm for achieving consensus among asynchronous processes that communicate by reading and writing shared registers. The fastest previously known algorithm has exponential expected running time. Our algorithm is polynomial, requiring an expected O(n 4
Randomized Protocols for Asynchronous Consensus
 Distributed Computing
, 2002
"... The famous Fischer, Lynch, and Paterson impossibility proof shows that it is impossible to solve the consensus problem in a natural model of an asynchronous distributed system if even a single process can fail. Since its publication, two decades of work on faulttolerant asynchronous consensus algor ..."
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Cited by 46 (1 self)
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algorithms have evaded this impossibility result by using extended models that provide (a) randomization, (b) additional timing assumptions, (c) failure detectors, or (d) stronger synchronization mechanisms than are available in the basic model. Concentrating on the first of these approaches, we illustrate
Automated Verification of a Randomized Distributed Consensus Protocol Using Cadence SMV and PRISM
, 2001
"... We consider the randomized consensus protocol of Aspnes and Herlihy for achieving agreement among N asynchronous processes that communicate via read/write shared registers. The algorithm guarantees termination in the presence of stopping failures within polynomial expected time. Processes proceed th ..."
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Cited by 26 (17 self)
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We consider the randomized consensus protocol of Aspnes and Herlihy for achieving agreement among N asynchronous processes that communicate via read/write shared registers. The algorithm guarantees termination in the presence of stopping failures within polynomial expected time. Processes proceed
sentationandproofoftherandomizedconsensusalgorithmofAspnesandHerlihy.The TheProbabilisticI/OAutomatonmodelof[20]isusedasthebasisforaformalpre RobertoSegalaz Abstract NancyLynch
"... algorithmguaranteesterminationwithinexpectedpolynomialtime. successionofasynchronousrounds,attemptingtoagreeateachround.Ateachround,the agreementattemptinvolvesadistributedrandomwalk.Thealgorithmishardtoanalyze becauseofitsuseofnontrivialresultsofprobabilitytheory(specically,randomwalk theory),becau ..."
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),becauseofitscomplexsetting,includingasynchronyandbothnondeterministic andprobabilisticchoice,andbecauseoftheinterplayamongseveraldierentsubprotocols. TheAspnesHerlihyalgorithmisarathercomplexalgorithm.Processesmovethrougha
Randomized Protocols for Asynchronous Consensus
, 2002
"... Abstract The famous Fischer, Lynch, and Paterson impossibility proof showsthat it is impossible to solve the consensus problem in a natural model of an asynchronous distributed system if even a single process canfail. Since its publication, two decades of work on faulttolerant asynchronous consensu ..."
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consensus algorithms have evaded this impossibility result byusing extended models that provide (a) randomization, (b) additional timing assumptions, (c) failure detectors, or (d) stronger synchronization mechanisms than are available in the basic model. Concentrating on the first of these approaches, we
Tight bounds for asynchronous randomized consensus
 In STOC ’07: Proceedings of the thirtyninth annual ACM symposium on Theory of computing
, 2007
"... A distributed consensus algorithm allows n processes to reach a common decision value starting from individual inputs. Waitfree consensus, in which a process always terminates within a finite number of its own steps, is impossible in an asynchronous sharedmemory system. However, consensus becomes ..."
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Cited by 22 (6 self)
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solvable using randomization when a process only has to terminate with probability 1. Randomized consensus algorithms are typically evaluated by their total step complexity, which is the expected total number of steps taken by all processes. This work proves that the total step complexity of randomized
Results 1  10
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242