%0 Journal Article
%T Study of Stationary Load Increase of Computer-Network Traffic via Dynamic Principal-Component Analysis
%A Shengkun Xie
%A Anna T. Lawniczak
%J ISRN Computational Mathematics
%D 2012
%R 10.5402/2012/103509
%X Many network monitoring applications and performance analysis tools are based on the study of an aggregate measure of network traffic, for example, number of packets in transit (NPT). The simulation modeling and analysis of this type of performance indicator enables a theoretical investigation of the underlying complex system through different combination of network setups such as routing algorithms, network source loads or network topologies. To detect stationary increase of network source load, we propose a dynamic principal component analysis (PCA) method, first to extract data features and then to detect a stationary load increase. The proposed detection schemes are based on either the major or the minor principal components of network traffic data. To demonstrate the applications of the proposed method, we first applied them to some synthetic data and then to network traffic data simulated from the packet switching network (PSN) model. The proposed detection schemes, based on dynamic PCA, show enhanced performance in detecting an increase of network load for the simulated network traffic data. These results show usefulness of a new feature extraction method based on dynamic PCA that creates additional feature variables for event detection in a univariate time series. 1. Introduction The dynamics of many complex systems such as computer networks, financial systems, transportation systems, or power systems are mathematically intractable due to their complexity ([1¨C3]). Better understanding of states of the complex systems and how these states change is accomplished by analyzing the data coming from the underlying complex systems [4]. In network system performance analysis, the traffic data is measured over time and statistical quality control techniques such as process control are often applied to detect whether thresholds are exceeded based on the standard deviations of observed variables. Statistical process control is the application of statistical methods such as principal component analysis (PCA) to the monitoring and control of a process to ensure that it operates at its full potential to produce conforming product. Monitoring the changes of traffic load is a practical issue to ensure that network systems are not overridden by users [5], in particular, when the load increase is stationary. We define the stationary load increase as a state of network traffic that is before the phase transition. The phase transition is due to a large increase of network source load so that the amount of network traffic appears to be increasing upward. That is,
%U http://www.hindawi.com/journals/isrn.computational.mathematics/2012/103509/