Social Network Behaviour Inferred from O-D Pair Traffic
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Keywords
Social Network, Origin–Destination, Traffic Matrix, Principal Component Analysis
Abstract
All network traffic is a by-product of social networking behaviour. In this paper, Anonymized Internet (IP) Trace Datasets obtained from the Center for Applied Internet Data Analysis (CAIDA) have been used to identify and estimate characteristics of the underlying social network from the overall traffic. The analysis methods used here fall into two groups, the first being based on frequency analysis and second method being based on the use of traffic matrices, with the later analysis method being further sub-divided into groups based on the traffic mean, variance and co-variance. The frequency analysis of origin (O), destination (D) and O-D Pair statistics exhibit heavy tailed behaviour. Because the large number of IP addresses contained in the CAIDA Datasets, only the most predominate IP Addresses are used when estimating all three sub-divided groups of traffic matrices. Principal Component Analysis (PCA) and related methods are applied to identify key features of each type of traffic matrix. A new system called Antraff has been developed to carry out all the analysis procedures.
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References
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Copyright Telecommunications Association Inc.
Mostfa Mohsin Albdair, University of Southern Queensland
Mostfa Mohsin Albdair was born January 1, 1974 in Thi-Qar, Iraq. He did his undergraduate work at College of Education for Pure Science / Ibn al-Haytham - University of Baghdad, Baghdad, Iraq in 1996. After college he got a job as physics teacher in Yemen from 2001 to 2005. Then he came back to Iraq and worked as physics teacher between 2005 and 2008.
After that He received his master degree from Malaysia in 2010 in Information and communication Technology he began work on his Master of ICT in Mesan University, Iraq as assistant Director of Computer Center. He strated his PhD study on October 2013 till now.
Ronald Addie, University of Southern Queensland
Ron Addie received his BSc degree from Monash University in 1972 and completed his PhD at Monash University in the area of semi-Markov queues in 1986. From 1972 to 1992, he worked in Telecom Australia Research Laboratories where he was involved in the development of ATM, teletraffic, and network analysis and design.In 1992 he moved to the University of Southern Queensland, where he is holds the position of Associate Professor.His current research interests include queueing theory for long-range dependent traffic, rare event simulation, layered network design, network analysis, design and simu lation software and security of web information systems. He is the author or co-author of many journal and conference papers, primarily in the area of communications, with more 1000 citations (according to Google Scholar).David Fatseas, University of Southern Queensland
David Fatseas was born in Brisbane, Australia in 1963. He received the Bachelor of Engineering Degree in Electronics and Communications from the Queensland Institute of Technology in 1986, a Master of Engineering and Technology Management Degree from the University of Queensland in 1995 and a Master of Computing Degree from the University of Southern Queensland in 2013. Over the past 30 years, he has held positions with a number of Major Telecommunication Equipment Vendors and Mobile Network Operators throughout Europe, Mid-East, Asia and Australia. During the majority of the time spent in these roles, he has lead the transmission fronthaul and backhaul solution development and deployment activities for 1G, 2G, 3G, 4G and 5G Radio Access Networks. His research interests include evolving transport network architectures, the dynamics of network traffic behavior, network trend prediction and statistical methods, network instrumentation and real-time traffic analytics methods, and high accuracy network synchronization. David is a Member of IEEE and is currently completing his PhD Studies at the University of Southern Queensland.
