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Entropy 2016, 18(1), 32; doi:10.3390/e18010032

Predicting Traffic Flow in Local Area Networks by the Largest Lyapunov Exponent

School of Mechanical Engineering, Northwestern Polytechnical University, Xi’an 710072, China
School of Energy and Power Engineering, Xi’an Jiaotong University, Xi’an 710049, China
Author to whom correspondence should be addressed.
Academic Editor: J. A. Tenreiro Machado
Received: 2 November 2015 / Revised: 6 January 2016 / Accepted: 11 January 2016 / Published: 19 January 2016
(This article belongs to the Special Issue Complex and Fractional Dynamics)
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The dynamics of network traffic are complex and nonlinear, and chaotic behaviors and their prediction, which play an important role in local area networks (LANs), are studied in detail, using the largest Lyapunov exponent. With the introduction of phase space reconstruction based on the time sequence, the high-dimensional traffic is projected onto the low dimension reconstructed phase space, and a reduced dynamic system is obtained from the dynamic system viewpoint. Then, a numerical method for computing the largest Lyapunov exponent of the low-dimensional dynamic system is presented. Further, the longest predictable time, which is related to chaotic behaviors in the system, is studied using the largest Lyapunov exponent, and the Wolf method is used to predict the evolution of the traffic in a local area network by both Dot and Interval predictions, and a reliable result is obtained by the presented method. As the conclusion, the results show that the largest Lyapunov exponent can be used to describe the sensitivity of the trajectory in the reconstructed phase space to the initial values. Moreover, Dot Prediction can effectively predict the flow burst. The numerical simulation also shows that the presented method is feasible and efficient for predicting the complex dynamic behaviors in LAN traffic, especially for congestion and attack in networks, which are the main two complex phenomena behaving as chaos in networks. View Full-Text
Keywords: LAN; phase space reconstruction; low dimensional dynamic system; largest Lyapunov exponent; prediction LAN; phase space reconstruction; low dimensional dynamic system; largest Lyapunov exponent; prediction

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Liu, Y.; Zhang, J. Predicting Traffic Flow in Local Area Networks by the Largest Lyapunov Exponent. Entropy 2016, 18, 32.

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