Solving the at-most-once problem with nearly optimal effectiveness

Kentros, Sotirios; Kiayias, Aggelos

doi:10.1145/1993806.1993847

Cited by 3 publications

(5 citation statements)

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“…However, their algorithm uses a collection of q permutations with contention O(q log q) and it is not known to date how to construct such permutations in polynomial time (see the discussion in the related work section). Finally, subsequent to the conference version of this paper [25], Alistarh et al [2] show that there exists a deterministic algorithm for the Write-All problem with work O(n + m log 5 n log 2 max(n, m)). Their solution is so far existential, while ours explicit.…”

Section: Contributionsmentioning

confidence: 99%

“…Following the conference version of this paper [25] and motivated by the difficulty of implementing wait-free deterministic solutions for the at-most-once problem that are effectiveness optimal, Kentros et al [24] introduced the strong at-most-once problem and studied its feasibility. The strong at-most-once problem refers to the setting where effectiveness is measured only in terms of the jobs that need to be executed and the processes that took part in the computation and crashed.…”

Section: Introductionmentioning

confidence: 99%

“…Although an efficient polynomial time construction of permutations with contention O(q polylog q) has been developed by Kowalski et al [27], it is not known to date how to construct permutations with contention O(q log q) in polynomial time. Subsequent to the conference version of this paper [25], Alistarh et al [2] show that there exists a deterministic algorithm for the Write-All problem with work O(n + m log 5 n log 2 max(n, m)), by derandomizing their randomized solution for the problem. Their solution is a breakthrough in terms of bridging the gap between the Ω (n + m log m) lower bound for the Write-All problem and known deterministic solutions, but is so far existential.…”

Section: Introductionmentioning

confidence: 99%

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Solving the at-most-once problem with nearly optimal effectiveness

Kentros

Kiayias

2013

Theoretical Computer Science

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We present and analyze a wait-free deterministic algorithm for solving the at-most-once problem: how m shared-memory fail-prone processes perform asynchronously n jobs at most once. Our algorithmic strategy provides for the first time nearly optimal effectiveness, which is a measure that expresses the total number of jobs completed in the worst case. The effectiveness of our algorithm equals n − 2m + 2. This is up to an additive factor of m close to the known effectiveness upper bound n − m + 1 over all possible algorithms and improves on the previously best known deterministic solutions that have effectiveness only n − log m · o(n). We also present an iterative version of our algorithm that for any m = O( 3+ǫ n/ log n) is both effectiveness-optimal and work-optimal, for any constant ǫ > 0. We then employ this algorithm to provide a new algorithmic solution for the Write-All problem which is work optimal for any m = O( 3+ǫ n/ log n). 1The problem becomes very challenging for autonomous processes in a system with concurrent invocations on multiple objects. At-most-once semantics have been thoroughly studied in the context of at-most-once message delivery [8,30,33] and at-most-once process invocation for RPC [6,31,37]. However, finding effective solutions for asynchronous shared-memory multiprocessors, in terms of how many at-most-once invocations can be performed by the cooperating processes, is largely an open problem. Solutions for the at-most-once problem, using only atomic read/write memory, and without specialized hardware support such as conditional writing, provide a useful tool in reasoning about the safety properties of applications developed for a variety of multiprocessor systems, including those not supporting bus-interlocking instructions and multi-core systems. Specifically, in recent years, attention has shifted from increasing clock speed towards chip multiprocessing, in order to increase the performance of systems. Because of the differences in each multi-core system, asynchronous shared memory is becoming an important abstraction for arguing about the safety properties of parallel applications in such systems. In the next years, one can expect chip multiprocessing to appear in a wide range of applications, many of which will have components that need to satisfy at-most-once semantics in order to guarantee safety. Such applications may include autonomous robotic devices, robotic devices for assisted living, automation in production lines or medical facilities. In such applications performing specific jobs at-most-once may be of paramount importance for safety of patients, the workers in a facility, or the devices themselves. Such jobs could be the triggering of a motor in a robotic arm, the activation of the X-ray gun in an X-ray machine, or supplying a dosage of medicine to a patient.Perhaps the most important question in this area is devising algorithms for the at-most-once problem with good effectiveness. The complexity measure of effectiveness [26] describes the number of jobs completed (at-mo...

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Section: Contributionsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Solving the at-most-once problem with nearly optimal effectiveness

Kentros

Kiayias

2013

Theoretical Computer Science

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“…Since there are few surviving processors, algorithm Modified-Det-Perm used in Part-One may not complete all tasks. Using the same derivation as for bound (41), the effort is O t + ∆ 1 p log 2 p up to the round when the number of active processors falls below p − f 1 . The contribution to work of the remaining rounds of Part-One is…”

Section: The Time Of the Main Extended Epochsmentioning

confidence: 99%

“…They gave a lower bound on the number of performed tasks, showing that it was impossible to perform all tasks, and gave an algorithm with effectiveness close to the lower bound. Kentros and Kiayias [41] solve At-Most-Once with improved effectiveness. Kentros et al [40] introduced the Strong-At-Most-Once problem, in which all tasks must be performed in the absence of crashes, and showed that it has consensus number 2.…”

Section: Introductionmentioning

confidence: 99%

Doing-it-All with bounded work and communication

Chlebus

Gąsieniec

Kowalski

et al. 2017

Information and Computation

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We consider the Do-All problem, where p cooperating processors need to complete t similar and independent tasks in an adversarial setting. Here we deal with a synchronous message passing system with processors that are subject to crash failures. Efficiency of algorithms in this setting is measured in terms of work complexity (also known as total available processor steps) and communication complexity (total number of point-to-point messages). When work and communication are considered to be comparable resources, then the overall efficiency is meaningfully expressed in terms of effort defined as work + communication. We develop and analyze a constructive algorithm that has work O(t + p log p ( √ p log p + √ t log t )) and a nonconstructive algorithm that has work O(t + p log 2 p). The latter result is close to the lower bound Ω(t + p log p/ log log p) on work. The effort of each of these algorithms is proportional to its work when the number of crashes is bounded above by c p, for some positive constant c < 1. We also present a nonconstructive algorithm that has effort O(t + p 1.77 ). The results of this paper were announced in a preliminary form in [11] and published in their final version as [10].

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Solving the At-Most-Once Problem with Nearly Optimal Effectiveness

Kentros

Kiayias

2012

Distributed Computing and Networking

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Solving the at-most-once problem with nearly optimal effectiveness

Cited by 3 publications

References 3 publications

Solving the at-most-once problem with nearly optimal effectiveness

Solving the at-most-once problem with nearly optimal effectiveness

Doing-it-All with bounded work and communication

Solving the At-Most-Once Problem with Nearly Optimal Effectiveness

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