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Trace Analysis Exploration Using Semantic Web Tools Use Case: You Tube Network Traffic

Authors:
Oscar Alberto Santana Alvarez
Liliana Ibeth Barbosa Santillán
Gerardo Padilla Zárate

Keywords: Network Traffic Traces; Semantic Analysis; Local Area Networks.

Abstract:
Analysis and exploration of information gathered through local networks are tasks that must constantly be done. Such information is useful for the local network administrators because it gives them a good input about the most effective maintenance procedure for the local network. Maintenance may include activities such as watching over preferences among users, keeping track of the size of the files users are accessing, most viewed videos, etc. It is especially important to watch over Video On Demand (VoD) traffic, such as YouTube-like services providers because of the size of the files they handle and their popularity among users, especially students. One approach to address monitoring activities is network traffic traces, which are sequences of events that recorded specific aspects of a web site. Such traces are usually stored as plain text files (i.e., logs). This paper presents the trace analysis exploration using semantic Web tools, with focus on the You Tube Network Traffic approach, which is based on semantic methods in facilitating network trace analysis by populating two Network Traffic Trace Turtle Files (NTTTF) with network traces obtained by monitoring means. The queries used over the NTTTFs allow us to identify key information presented in the network traffic trace associated with different aspects of our case study. The results showed the feasibility of this approach, where NTTFs improved the way valuable information is being found. Analysis of network traces showed information such as the most viewed videos, the slowest YouTube servers, etc. With this information, more accurate maintenance procedures can be followed. The analysis and exploration of approximately 1,100,000 (one million one hundred thousand) YouTube network traffic traces was performed by means of semantic queries.

Pages: 89 to 95

Copyright: Copyright (c) IARIA, 2014

Publication date: July 20, 2014

Published in: conference

ISSN: 2326-9332

ISBN: 978-1-61208-364-3

Location: Paris, France

Dates: from July 20, 2014 to July 24, 2014