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

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14610%2F16%3A00106981" target="_blank" >RIV/00216224:14610/16:00106981 - isvavai.cz</a>

  • Result on the web

    <a href="http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7502952" target="_blank" >http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7502952</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1109/NOMS.2016.7502952" target="_blank" >10.1109/NOMS.2016.7502952</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

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

  • Original language description

    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.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2016

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium

  • ISBN

    9781509002238

  • ISSN

    1542-1201

  • e-ISSN

  • Number of pages

    2

  • Pages from-to

    1019-1020

  • Publisher name

    IEEE Xplore Digital Library

  • Place of publication

    Istanbul, Turkey

  • Event location

    Istanbul, Turkey

  • Event date

    Apr 25, 2016

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    000389830100163