NDLI: Analysis of network node behavior based on MapReduce

Content Provider	IEEE Xplore Digital Library
Author	Gang He Peng Yang Xiaochun Wu
Copyright Year	2014
Description	Author affiliation: Beijing Key Lab. of Network Syst. Archit. & Convergence, Beijing Univ. of Posts & Telecommun., Beijing, China (Gang He; Peng Yang; Xiaochun Wu)
Abstract	With the widespread popularity and rapid development of Internet, the network is becoming more complex. Analysis of network node behavior can be crucial for network management and service provisioning. In this paper, we conduct the detailed measurement analysis of the network node (NN) traffic characteristics based on a large-scale data set collected from an enterprise network traffic monitoring device, which is deployed at the entry of enterprise network covering the Guangdong province in China. We analyze the distribution of NN traffic volume and visitor number. We discuss the rank of NN in terms of traffic volume distribution and visitor number distribution, which follows power law distribution. Furthermore, we illustrate the traffic characteristics of NN in terms of visitor number. To handle the problem of big data processing, we make use of Hadoop framework and MapReduce programming model to analyze huge traffic data, which handles a large collection data efficiently and quickly for scalable storage and analysis. Thus, in this paper, we propose a network traffic analysis method based on MapReduce in enterprise internet.
Starting Page	193
Ending Page	197
File Size	188446
Page Count	5
File Format	PDF
ISBN	9781479947201
e-ISBN	9781479947195
DOI	10.1109/CCIS.2014.7175728
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-11-27
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	NN Artificial neural networks Telecommunication traffic Programming Visitor number MapReduce Traffic volume Distributed databases Enterprise internet Big data Internet Probes Monitoring
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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