Abstract
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 tasks at most once. Our algorithmic strategy provides for the first time nearly optimal effectiveness, which is a measure that expresses the total number of tasks 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 − logm ·o(n). We also present an iterated version of our algorithm that for any \(m = \mathrm{O}(\sqrt[3+\epsilon]{n/\log n})\) is both effectiveness-optimal and work-optimal, for any constant ε > 0. We then employ this algorithm to provide a new algorithmic solution for the Write-All problem which is work optimal for any \(m=\mathrm{O}(\sqrt[3+\epsilon]{n/\log n})\).
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Kentros, S., Kiayias, A. (2012). Solving the At-Most-Once Problem with Nearly Optimal Effectiveness. In: Bononi, L., Datta, A.K., Devismes, S., Misra, A. (eds) Distributed Computing and Networking. ICDCN 2012. Lecture Notes in Computer Science, vol 7129. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25959-3_9
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DOI: https://doi.org/10.1007/978-3-642-25959-3_9
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