Contention resolution with constant throughput and log-logstar channel accesse

Michael A. Bender, Tsvi Kopelowitz, Seth Pettie, Maxwell Young

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

For decades, randomized exponential backoff has provided a critical algorithmic building block in situations where multiple devices seek access to a shared resource. Despite this history, the performance of standard exponential backoff is poor under worst-case scheduling of demands on the resource: (i) subconstant throughput can occur under plausible scenarios, and (ii) each of N devices requires Ω(log N) access attempts before obtaining the resource. In this paper, we address these shortcomings by offering a new backoff protocol for a shared communication channel that guarantees expected constant throughput with only O(log(log N)) channel accesses in expectation, even when packet arrivals are scheduled by an adversary. Central to this result are new algorithms for approximate counting and leader election with the same performance guarantees.

Original languageEnglish
Pages (from-to)1735-1754
Number of pages20
JournalSIAM Journal on Computing
Volume47
Issue number5
DOIs
StatePublished - 2018
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2018 Society for Industrial and Applied Mathematics

Funding

∗Received by the editors November 29, 2017; accepted for publication (in revised form) August 6, 2018; published electronically October 2, 2018. A preliminary version of our results appeared as an extended abstract at STOC’16, ACM, New York, pp. 499–508 [14]. http://www.siam.org/journals/sicomp/47-5/M115860.html Funding: This research was partially supported by National Science Foundation grants CCF-1217708, IIS-1247726, IIS-1251137, CNS-1408695, CCF-1439084, CCF-1217338, CNS-1318294, CCF-1514383, CNS-1318294, CCF-1613772, CCF-1815316, CCF-1617618, CCF-1763680, CCF-1716252, CCF-1725543, and CNS-1755615. Support is also provided by Sandia National Laboratories, NetApp, and a research gift from C Spire. This research was partially supported by National Science Foundation grants CCF-1217708, IIS-1247726, IIS-1251137, CNS-1408695, CCF-1439084, CCF-1217338, CNS-1318294, CCF-1514383, CNS-1318294, CCF-1613772, CCF-1815316, CCF-1617618, CCF-1763680, CCF-1716252, CCF-1725543, and CNS-1755615. Support is also provided by Sandia National Laboratories, NetApp, and a research gift from C Spire.

FundersFunder number
National Science FoundationCNS-1755615, CCF-1217338, CCF-1613772, CCF-1725543, CCF-1439084, CCF-1617618, CCF-1514383, CCF-1716252, CCF-1815316, IIS-1251137, CNS-1408695, 1637546, CNS-1318294, IIS-1247726, CCF-1217708, CCF-1763680
Sandia National Laboratories
National Science Foundation

    Keywords

    • Adversarial scheduling
    • Algorithms
    • Contention resolution
    • Distributed computing
    • Throughput
    • Wireless networks

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