Real-time Analysis of NetFlow Data for Generating Network
Traffic Statistics using Apache Spark

D 2016

Real-time Analysis of NetFlow Data for Generating Network Traffic Statistics using Apache Spark

ČERMÁK, Milan; Tomáš JIRSÍK a Martin LAŠTOVIČKA

Základní údaje

Originální název

Real-time Analysis of NetFlow Data for Generating Network Traffic Statistics using Apache Spark

Název česky

Analýza NetFlow dat pro tvorbu síťových statistik v reálném čase pomocí Apache Spark

Autoři

ČERMÁK, Milan; Tomáš JIRSÍK a Martin LAŠTOVIČKA

Vydání

Istanbul, Turkey, NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium, od s. 1019-1020, 2 s. 2016

Nakladatel

IEEE Xplore Digital Library

Další údaje

Jazyk

angličtina

Typ výsledku

Stať ve sborníku

Obor

10201 Computer sciences, information science, bioinformatics

Stát vydavatele

Spojené státy

Utajení

není předmětem státního či obchodního tajemství

Forma vydání

paměťový nosič (CD, DVD, flash disk)

Odkazy

URL

Označené pro přenos do RIV

Ano

Kód RIV

RIV/00216224:14610/16:00106981

Organizační jednotka

Ústav výpočetní techniky

ISBN

978-1-5090-0223-8

ISSN

Klíčová slova anglicky

Apache Spark;Real-time;Network Statistics

Příznaky

Mezinárodní význam, Recenzováno

Změněno: 22. 7. 2019 10:00, Mgr. Michal Petr

Anotace

V originále

Abstract—In this paper, we present a framework for the realtime generation of network traffic statistics on Apache Spark Streaming, a modern distributed stream processing system. Our previous results showed that stream processing systems provide enough throughput to process a large volume of NetFlow data and hence they are suitable for network traffic monitoring. This paper describes the integration of Apache Spark Streaming into a current network monitoring architecture. We prove that it is possible to implement the same basic methods for NetFlow data analysis in the stream processing framework as in the traditional ones. Moreover, our stream processing implementation discovers new information which is not available when using traditional network monitoring approaches.

Přiložené soubory

poster.pdf

paper.pdf

Citovat

ČERMÁK, Milan; Tomáš JIRSÍK a Martin LAŠTOVIČKA. Real-time Analysis of NetFlow Data for Generating Network Traffic Statistics using Apache Spark. In Sema Oktug, Mehmet Ulema, Cicek Cavdar, Lisandro Zambenedetti Granville, Carlos Raniery P. dos Santos. NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium. Istanbul, Turkey: IEEE Xplore Digital Library, 2016, s. 1019-1020. ISBN 978-1-5090-0223-8. Dostupné z: https://doi.org/10.1109/NOMS.2016.7502952.

@inproceedings{1334784,
   author = {Čermák, Milan and Jirsík, Tomáš and Laštovička, Martin},
   address = {Istanbul, Turkey},
   booktitle = {NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium},
   doi = {https://doi.org/10.1109/NOMS.2016.7502952},
   editor = {Sema Oktug, Mehmet Ulema, Cicek Cavdar, Lisandro Zambenedetti Granville, Carlos Raniery P. dos Santos},
   keywords = {Apache Spark;Real-time;Network Statistics},
   howpublished = {paměťový nosič},
   language = {eng},
   location = {Istanbul, Turkey},
   isbn = {978-1-5090-0223-8},
   pages = {1019-1020},
   publisher = {IEEE Xplore Digital Library},
   title = {Real-time Analysis of NetFlow Data for Generating Network Traffic Statistics using Apache Spark},
   url = {http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7502952},
   year = {2016}
}

TY  - CONF
ID  - 1334784
AU  - Čermák, Milan - Jirsík, Tomáš - Laštovička, Martin
PY  - 2016
TI  - Real-time Analysis of NetFlow Data for Generating Network Traffic Statistics using Apache Spark
PB  - IEEE Xplore Digital Library
CY  - Istanbul, Turkey
SN  - 9781509002238
KW  - Apache Spark;Real-time;Network Statistics
UR  - http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7502952
L2  - http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7502952
N2  - Abstract—In this paper, we present a framework for the realtime generation of network traffic statistics on Apache Spark Streaming, a modern distributed stream processing system. Our previous results showed that stream processing systems provide enough throughput to process a large volume of NetFlow data and hence they are suitable for network traffic monitoring. This paper describes the integration of Apache Spark Streaming into a current network monitoring architecture. We prove that it is possible to implement the same basic methods for NetFlow data analysis in the stream processing framework as in the traditional ones. Moreover, our stream processing implementation discovers new information which is not available when using traditional network monitoring approaches.
ER  -

ČERMÁK, Milan; Tomáš JIRSÍK a Martin LAŠTOVIČKA. Real-time Analysis of NetFlow Data for Generating Network Traffic Statistics using Apache Spark. In Sema Oktug, Mehmet Ulema, Cicek Cavdar, Lisandro Zambenedetti Granville, Carlos Raniery P. dos Santos. \textit{NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium}. Istanbul, Turkey: IEEE Xplore Digital Library, 2016, s.~1019-1020. ISBN~978-1-5090-0223-8. Dostupné z: https://doi.org/10.1109/NOMS.2016.7502952.

Přehled o publikaci