Pay for a Sliding Bloom Filter and Get Counting, Distinct Elements, and Entropy for Free

Eran Assaf; Ran Ben Basat; Gil Einziger; Roy Friedman

doi:10.1109/INFOCOM.2018.8485882

Pay for a Sliding Bloom Filter and Get Counting, Distinct Elements, and Entropy for Free

Eran Assaf, Ran Ben Basat, Gil Einziger, Roy Friedman

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

36 Scopus citations

Abstract

For many networking applications, recent data is more significant than older data, motivating the need for sliding window solutions. Various capabilities, such as DDoS detection and load balancing, require insights about multiple metrics including Bloom filters, per-flow counting, count distinct and entropy estimation. In this work, we present a unified construction that solves all the above problems in the sliding window model. Our single solution offers a better space to accuracy tradeoff than the state-of-the-art for each of these individual problems We show this both analytically and by running multiple real Internet backbone and datacenter packet traces.

Original language	English
Title of host publication	INFOCOM 2018 - IEEE Conference on Computer Communications
Publisher	Institute of Electrical and Electronics Engineers
Pages	2204-2212
Number of pages	9
ISBN (Electronic)	9781538641286
DOIs	https://doi.org/10.1109/INFOCOM.2018.8485882
State	Published - 8 Oct 2018
Externally published	Yes
Event	2018 IEEE Conference on Computer Communications, INFOCOM 2018 - Honolulu, United States Duration: 15 Apr 2018 → 19 Apr 2018

Publication series

Name	Proceedings - IEEE INFOCOM
Volume	2018-April
ISSN (Print)	0743-166X

Conference

Conference	2018 IEEE Conference on Computer Communications, INFOCOM 2018
Country/Territory	United States
City	Honolulu
Period	15/04/18 → 19/04/18

ASJC Scopus subject areas

General Computer Science
Electrical and Electronic Engineering

Access to Document

10.1109/INFOCOM.2018.8485882

Cite this

Assaf, E., Basat, R. B., Einziger, G., & Friedman, R. (2018). Pay for a Sliding Bloom Filter and Get Counting, Distinct Elements, and Entropy for Free. In INFOCOM 2018 - IEEE Conference on Computer Communications (pp. 2204-2212). Article 8485882 (Proceedings - IEEE INFOCOM; Vol. 2018-April). Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/INFOCOM.2018.8485882

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title = "Pay for a Sliding Bloom Filter and Get Counting, Distinct Elements, and Entropy for Free",

abstract = "For many networking applications, recent data is more significant than older data, motivating the need for sliding window solutions. Various capabilities, such as DDoS detection and load balancing, require insights about multiple metrics including Bloom filters, per-flow counting, count distinct and entropy estimation. In this work, we present a unified construction that solves all the above problems in the sliding window model. Our single solution offers a better space to accuracy tradeoff than the state-of-the-art for each of these individual problems We show this both analytically and by running multiple real Internet backbone and datacenter packet traces.",

author = "Eran Assaf and Basat, {Ran Ben} and Gil Einziger and Roy Friedman",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 2018 IEEE Conference on Computer Communications, INFOCOM 2018 ; Conference date: 15-04-2018 Through 19-04-2018",

year = "2018",

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doi = "10.1109/INFOCOM.2018.8485882",

language = "English",

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Assaf, E, Basat, RB, Einziger, G & Friedman, R 2018, Pay for a Sliding Bloom Filter and Get Counting, Distinct Elements, and Entropy for Free. in INFOCOM 2018 - IEEE Conference on Computer Communications., 8485882, Proceedings - IEEE INFOCOM, vol. 2018-April, Institute of Electrical and Electronics Engineers, pp. 2204-2212, 2018 IEEE Conference on Computer Communications, INFOCOM 2018, Honolulu, United States, 15/04/18. https://doi.org/10.1109/INFOCOM.2018.8485882

Pay for a Sliding Bloom Filter and Get Counting, Distinct Elements, and Entropy for Free. / Assaf, Eran; Basat, Ran Ben; Einziger, Gil et al.
INFOCOM 2018 - IEEE Conference on Computer Communications. Institute of Electrical and Electronics Engineers, 2018. p. 2204-2212 8485882 (Proceedings - IEEE INFOCOM; Vol. 2018-April).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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Y1 - 2018/10/8

N2 - For many networking applications, recent data is more significant than older data, motivating the need for sliding window solutions. Various capabilities, such as DDoS detection and load balancing, require insights about multiple metrics including Bloom filters, per-flow counting, count distinct and entropy estimation. In this work, we present a unified construction that solves all the above problems in the sliding window model. Our single solution offers a better space to accuracy tradeoff than the state-of-the-art for each of these individual problems We show this both analytically and by running multiple real Internet backbone and datacenter packet traces.

AB - For many networking applications, recent data is more significant than older data, motivating the need for sliding window solutions. Various capabilities, such as DDoS detection and load balancing, require insights about multiple metrics including Bloom filters, per-flow counting, count distinct and entropy estimation. In this work, we present a unified construction that solves all the above problems in the sliding window model. Our single solution offers a better space to accuracy tradeoff than the state-of-the-art for each of these individual problems We show this both analytically and by running multiple real Internet backbone and datacenter packet traces.

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M3 - Conference contribution

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BT - INFOCOM 2018 - IEEE Conference on Computer Communications

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ER -

Pay for a Sliding Bloom Filter and Get Counting, Distinct Elements, and Entropy for Free

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