Long-lived counters with polylogarithmic amortized step complexity
Baig MA, Hendler D, Milani A, Travers C. 2023. Long-lived counters with polylogarithmic amortized step complexity. Distributed Computing. 36, 29–43.
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Author
Baig, Mirza AhadISTA;
Hendler, Danny;
Milani, Alessia;
Travers, Corentin
Department
Abstract
A shared-memory counter is a widely-used and well-studied concurrent object. It supports two operations: An Inc operation that increases its value by 1 and a Read operation that returns its current value. In Jayanti et al (SIAM J Comput, 30(2), 2000), Jayanti, Tan and Toueg proved a linear lower bound on the worst-case step complexity of obstruction-free implementations, from read-write registers, of a large class of shared objects that includes counters. The lower bound leaves open the question of finding counter implementations with sub-linear amortized step complexity. In this work, we address this gap. We show that n-process, wait-free and linearizable counters can be implemented from read-write registers with O(log2n) amortized step complexity. This is the first counter algorithm from read-write registers that provides sub-linear amortized step complexity in executions of arbitrary length. Since a logarithmic lower bound on the amortized step complexity of obstruction-free counter implementations exists, our upper bound is within a logarithmic factor of the optimal. The worst-case step complexity of the construction remains linear, which is optimal. This is obtained thanks to a new max register construction with O(logn) amortized step complexity in executions of arbitrary length in which the value stored in the register does not grow too quickly. We then leverage an existing counter algorithm by Aspnes, Attiya and Censor-Hillel [1] in which we “plug” our max register implementation to show that it remains linearizable while achieving O(log2n) amortized step complexity.
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Publishing Year
Date Published
2023-03-01
Journal Title
Distributed Computing
Publisher
Springer Nature
Acknowledgement
A preliminary version of this work appeared in DISC’19. Mirza Ahad Baig, Alessia Milani and Corentin Travers are supported by ANR projects Descartes and FREDDA. Mirza Ahad Baig is supported by UMI Relax. Danny Hendler is supported by the Israel Science Foundation (Grants 380/18 and 1425/22).
Volume
36
Page
29-43
ISSN
eISSN
IST-REx-ID
Cite this
Baig MA, Hendler D, Milani A, Travers C. Long-lived counters with polylogarithmic amortized step complexity. Distributed Computing. 2023;36:29-43. doi:10.1007/s00446-022-00439-5
Baig, M. A., Hendler, D., Milani, A., & Travers, C. (2023). Long-lived counters with polylogarithmic amortized step complexity. Distributed Computing. Springer Nature. https://doi.org/10.1007/s00446-022-00439-5
Baig, Mirza Ahad, Danny Hendler, Alessia Milani, and Corentin Travers. “Long-Lived Counters with Polylogarithmic Amortized Step Complexity.” Distributed Computing. Springer Nature, 2023. https://doi.org/10.1007/s00446-022-00439-5.
M. A. Baig, D. Hendler, A. Milani, and C. Travers, “Long-lived counters with polylogarithmic amortized step complexity,” Distributed Computing, vol. 36. Springer Nature, pp. 29–43, 2023.
Baig MA, Hendler D, Milani A, Travers C. 2023. Long-lived counters with polylogarithmic amortized step complexity. Distributed Computing. 36, 29–43.
Baig, Mirza Ahad, et al. “Long-Lived Counters with Polylogarithmic Amortized Step Complexity.” Distributed Computing, vol. 36, Springer Nature, 2023, pp. 29–43, doi:10.1007/s00446-022-00439-5.
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