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Single Update Sketch with Variable Counter Structure

Research output: Contribution to journalConference articlepeer-review

13 Citations (SciVal)

Abstract

Per-flow size measurement is key to many streaming applications and management systems, particularly in high-speed networks. Performing such measurement on the data plane of a network device at the line rate requires on-chip memory and computing resources that are shared by other key network functions. It leads to the need for very compact and fast data structures, called sketches, which trade off space for accuracy. Such a need also arises in other application context for extremely large data sets. The goal of sketch design is two-fold: to measure flow size as accurately as possible and to do so as efficiently as possible (for low overhead and thus high processing throughput). The existing sketches can be broadly categorized to multi-update sketches and single update sketches. The former are more accurate but carry larger overhead. The latter incur small overhead but their accuracy is poor. This paper proposes a Single update Sketch with a Variable counter Structure (SSVS), a new sketch design which is several times faster than the existing multi-update sketches with comparable accuracy, and is several times more accurate than the existing single update sketches with comparable overhead. The new sketch design embodies several technical contributions that integrate the enabling properties from both multi-update sketches and single update sketches in a novel structure that effectively controls the measurement error with minimum processing overhead.

Original languageEnglish
Pages (from-to)4296-4309
Number of pages14
JournalProceedings of the VLDB Endowment
Volume16
Issue number13
DOIs
StatePublished - 2023
Event49th International Conference on Very Large Data Bases, VLDB 2023 - Vancouver, Canada
Duration: Aug 28 2023Sep 1 2023

Bibliographical note

Publisher Copyright:
© 2023, VLDB Endowment. All rights reserved.

Funding

This work is supported in part by National Science Foundation under grants CNS 1909077 and CNS-2312676.

FundersFunder number
National Science Foundation Arctic Social Science ProgramCNS 1909077, CNS-2312676

    ASJC Scopus subject areas

    • Computer Science (miscellaneous)
    • General Computer Science

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