Heavy hitters in streams and sliding windows

Ran Ben-Basat; Gil Einziger; Roy Friedman; Yaron Kassner

doi:10.1109/INFOCOM.2016.7524364

Heavy hitters in streams and sliding windows

Ran Ben-Basat, Gil Einziger, Roy Friedman, Yaron Kassner

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

139 Scopus citations

Abstract

Identifying heavy hitter flows is a fundamental problem in various network domains. The well established method of using sketches to approximate flow statistics suffers from space inefficiencies. In addition, flow arrival rates are dynamic, thus keeping track of the most recent heavy hitters poses a challenge. Sliding window approximations address this problem, reducing space at the cost of increasing point query time. This paper presents two novel algorithms for identifying heavy hitters in streams and sliding windows. Both algorithms use statically allocated memory and support constant time point queries. For sliding windows, this is an asymptotic improvement over previous work. We also demonstrate reduced memory requirements of up to 85% in streams and 66% in sliding windows over synthetic and real Internet packet traces.

Original language	English
Title of host publication	IEEE INFOCOM 2016 - 35th Annual IEEE International Conference on Computer Communications
Publisher	Institute of Electrical and Electronics Engineers
ISBN (Electronic)	9781467399531
DOIs	https://doi.org/10.1109/INFOCOM.2016.7524364
State	Published - 27 Jul 2016
Externally published	Yes
Event	35th Annual IEEE International Conference on Computer Communications, IEEE INFOCOM 2016 - San Francisco, United States Duration: 10 Apr 2016 → 14 Apr 2016

Publication series

Name	Proceedings - IEEE INFOCOM
Volume	2016-July
ISSN (Print)	0743-166X

Conference

Conference	35th Annual IEEE International Conference on Computer Communications, IEEE INFOCOM 2016
Country/Territory	United States
City	San Francisco
Period	10/04/16 → 14/04/16

ASJC Scopus subject areas

General Computer Science
Electrical and Electronic Engineering

Access to Document

10.1109/INFOCOM.2016.7524364

Cite this

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title = "Heavy hitters in streams and sliding windows",

abstract = "Identifying heavy hitter flows is a fundamental problem in various network domains. The well established method of using sketches to approximate flow statistics suffers from space inefficiencies. In addition, flow arrival rates are dynamic, thus keeping track of the most recent heavy hitters poses a challenge. Sliding window approximations address this problem, reducing space at the cost of increasing point query time. This paper presents two novel algorithms for identifying heavy hitters in streams and sliding windows. Both algorithms use statically allocated memory and support constant time point queries. For sliding windows, this is an asymptotic improvement over previous work. We also demonstrate reduced memory requirements of up to 85% in streams and 66% in sliding windows over synthetic and real Internet packet traces.",

author = "Ran Ben-Basat and Gil Einziger and Roy Friedman and Yaron Kassner",

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year = "2016",

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doi = "10.1109/INFOCOM.2016.7524364",

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Ben-Basat, R, Einziger, G, Friedman, R & Kassner, Y 2016, Heavy hitters in streams and sliding windows. in IEEE INFOCOM 2016 - 35th Annual IEEE International Conference on Computer Communications., 7524364, Proceedings - IEEE INFOCOM, vol. 2016-July, Institute of Electrical and Electronics Engineers, 35th Annual IEEE International Conference on Computer Communications, IEEE INFOCOM 2016, San Francisco, United States, 10/04/16. https://doi.org/10.1109/INFOCOM.2016.7524364

Heavy hitters in streams and sliding windows. / Ben-Basat, Ran; Einziger, Gil; Friedman, Roy et al.
IEEE INFOCOM 2016 - 35th Annual IEEE International Conference on Computer Communications. Institute of Electrical and Electronics Engineers, 2016. 7524364 (Proceedings - IEEE INFOCOM; Vol. 2016-July).

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

TY - GEN

T1 - Heavy hitters in streams and sliding windows

AU - Ben-Basat, Ran

AU - Einziger, Gil

AU - Friedman, Roy

AU - Kassner, Yaron

PY - 2016/7/27

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N2 - Identifying heavy hitter flows is a fundamental problem in various network domains. The well established method of using sketches to approximate flow statistics suffers from space inefficiencies. In addition, flow arrival rates are dynamic, thus keeping track of the most recent heavy hitters poses a challenge. Sliding window approximations address this problem, reducing space at the cost of increasing point query time. This paper presents two novel algorithms for identifying heavy hitters in streams and sliding windows. Both algorithms use statically allocated memory and support constant time point queries. For sliding windows, this is an asymptotic improvement over previous work. We also demonstrate reduced memory requirements of up to 85% in streams and 66% in sliding windows over synthetic and real Internet packet traces.

AB - Identifying heavy hitter flows is a fundamental problem in various network domains. The well established method of using sketches to approximate flow statistics suffers from space inefficiencies. In addition, flow arrival rates are dynamic, thus keeping track of the most recent heavy hitters poses a challenge. Sliding window approximations address this problem, reducing space at the cost of increasing point query time. This paper presents two novel algorithms for identifying heavy hitters in streams and sliding windows. Both algorithms use statically allocated memory and support constant time point queries. For sliding windows, this is an asymptotic improvement over previous work. We also demonstrate reduced memory requirements of up to 85% in streams and 66% in sliding windows over synthetic and real Internet packet traces.

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M3 - Conference contribution

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T3 - Proceedings - IEEE INFOCOM

BT - IEEE INFOCOM 2016 - 35th Annual IEEE International Conference on Computer Communications

PB - Institute of Electrical and Electronics Engineers

T2 - 35th Annual IEEE International Conference on Computer Communications, IEEE INFOCOM 2016

Y2 - 10 April 2016 through 14 April 2016

ER -

Heavy hitters in streams and sliding windows

Abstract

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