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Owing to the explosive growth of Internet traffic, network operators must be able to monitor the entire network situation and efficiently manage their network resources. Traditional network analysis methods that usually work on a single machine are no longer suitable for huge traffic data owing to their poor processing ability. Big data frameworks, such as Hadoop and Spark, can handle such analysis jobs even for a large amount of network traffic. However, Hadoop and Spark are inherently designed for offline data analysis. To cope with streaming data, various stream-processing-based frameworks have been proposed, such as Storm, Flink, and Spark Streaming. In this study, we propose an online Internet traffic monitoring system based on Spark Streaming. The system comprises three parts, namely, the collector, messaging system, and stream processor. We considered the TCP performance monitoring as a special use case of showing how network monitoring can be performed with our proposed system. We conducted typical experiments with a cluster in standalone mode, which showed that our system performs well for large Internet traffic measurement and monitoring.


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Online Internet Traffic Monitoring System Using Spark Streaming

Show Author's information Baojun ZhouJie Li( )Xiaoyan WangYu GuLi XuYongqiang HuLihua Zhu
Department of Computer Science, University of Tsukuba, Tsukuba 305-8577, Japan.
College of Engineering, Ibaraki University, Hitachi 316-8511, Japan.
School of Computer and Information, Hefei University of Technology, Hefei 230601, China.
College of Mathematics and Computer Science, Fujian Normal University, Fuzhou 350007, China.
Institute of Scientific and Technical Information of Qinghai, Xining 810008, China.

Abstract

Owing to the explosive growth of Internet traffic, network operators must be able to monitor the entire network situation and efficiently manage their network resources. Traditional network analysis methods that usually work on a single machine are no longer suitable for huge traffic data owing to their poor processing ability. Big data frameworks, such as Hadoop and Spark, can handle such analysis jobs even for a large amount of network traffic. However, Hadoop and Spark are inherently designed for offline data analysis. To cope with streaming data, various stream-processing-based frameworks have been proposed, such as Storm, Flink, and Spark Streaming. In this study, we propose an online Internet traffic monitoring system based on Spark Streaming. The system comprises three parts, namely, the collector, messaging system, and stream processor. We considered the TCP performance monitoring as a special use case of showing how network monitoring can be performed with our proposed system. We conducted typical experiments with a cluster in standalone mode, which showed that our system performs well for large Internet traffic measurement and monitoring.

Keywords:

spark streaming, network monitoring, big data, TCP performance monitoring
Received: 11 August 2017 Accepted: 30 November 2017 Published: 25 January 2018 Issue date: March 2018
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Publication history

Received: 11 August 2017
Accepted: 30 November 2017
Published: 25 January 2018
Issue date: March 2018

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© The author(s) 2018

Acknowledgements

This work was partially supported by Grant-in-Aid for Scientific Research from Japan Society for Promotion of Science (JSPS), Qinghai Joint Research Grant (No. 2016-HZ-804), and Research Collaboration Grant from NII, Japan.

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