Skip to main navigation Skip to search Skip to main content

A faster and more efficient q-MAX algorithm

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    Abstract

    The q-MAX problem, which seeks to find the q largest elements in a data stream, has numerous networking applications including sketches, network-wide heavy hitters, and others. In this poster, we propose an improvement to the q-MAX algorithm [5] that leverages sampling to accelerate the computation. Despite being randomized, our algorithm never fails (i.e., it is a Las Vegas algorithm) and runs up to 62% faster when evaluated on real packet traces and tasks. Moreover, on a real networking application and workload, our algorithm provides an 11-53% higher throughput.

    Original languageEnglish
    Title of host publicationCoNEXT 2020 - Proceedings of the 16th International Conference on Emerging Networking EXperiments and Technologies
    PublisherAssociation for Computing Machinery, Inc
    Pages538-539
    Number of pages2
    ISBN (Electronic)9781450379489
    DOIs
    StatePublished - 23 Nov 2020
    Event16th ACM Conference on Emerging Networking Experiment and Technologies, CoNEXT 2020 - Barcelona, Spain
    Duration: 1 Dec 20204 Dec 2020

    Publication series

    NameCoNEXT 2020 - Proceedings of the 16th International Conference on Emerging Networking EXperiments and Technologies

    Conference

    Conference16th ACM Conference on Emerging Networking Experiment and Technologies, CoNEXT 2020
    Country/TerritorySpain
    CityBarcelona
    Period1/12/204/12/20

    Keywords

    • algorithms
    • data structures
    • measurement
    • monitoring

    ASJC Scopus subject areas

    • Computer Networks and Communications

    Fingerprint

    Dive into the research topics of 'A faster and more efficient q-MAX algorithm'. Together they form a unique fingerprint.

    Cite this