Optimal Estimation of Contour Properties by Cross-Validated Regularization
IEEE Transactions on Pattern Analysis and Machine Intelligence
On the self-similar nature of Ethernet traffic (extended version)
IEEE/ACM Transactions on Networking (TON)
Wide area traffic: the failure of Poisson modeling
IEEE/ACM Transactions on Networking (TON)
Experimental queueing analysis with long-range dependent packet traffic
IEEE/ACM Transactions on Networking (TON)
SIGMETRICS '98/PERFORMANCE '98 Proceedings of the 1998 ACM SIGMETRICS joint international conference on Measurement and modeling of computer systems
On the relevance of long-range dependence in network traffic
IEEE/ACM Transactions on Networking (TON)
Self-Similar Network Traffic and Performance Evaluation
Self-Similar Network Traffic and Performance Evaluation
A Multiplicative Multifractal Model for TCP Traffic
ISCC '01 Proceedings of the Sixth IEEE Symposium on Computers and Communications
On the variability of internet traffic
On the variability of internet traffic
Envelope process and computation of the equivalent bandwidth of multifractal flows
Computer Networks: The International Journal of Computer and Telecommunications Networking - Special issue: Long range dependent trafic
Theory, Volume 1, Queueing Systems
Theory, Volume 1, Queueing Systems
Infinitely divisible cascade analysis of network traffic data
ICASSP '00 Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 01
A wavelet-based joint estimator of the parameters of long-range dependence
IEEE Transactions on Information Theory
Scaling analysis of conservative cascades, with applications to network traffic
IEEE Transactions on Information Theory
A multifractal wavelet model with application to network traffic
IEEE Transactions on Information Theory
An approximation method of origin-destination flow traffic from link load counts
Computers and Electrical Engineering
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Commonly used measures of traffic burstiness do not capture the fluctuation of traffic variability over the entire range of time-scales. In this paper, we present a measure of variability, called the Index of Variability (Hv(τ)), that depicts the degree of variability (burstiness) of a typical network traffic process at each time-scale and is analytically tractable for many traffic models. As an illustration, we derive the closed-form expressions of Hv(τ) for two traditional traffic models and generate a variety of two-dimensional (2D) and three-dimensional (3D) Index-of-Variability curves. These curves demonstrate that the Index of Variability can help in determining the complexities of the network traffic variability over the network performance relevant time-scales. We then introduce a practical method for estimating the Index-of-Variability curve from a given traffic trace. Using this method, we estimate the Index-of-Variability curves for 12 long NLANR network traffic traces. The results indicate that the variability of real network traffic varies with time-scales and that the Index of Variability has the ability to discern qualitative differences between traffic traces obtained from different networks. Thus, the Index of Variability offers the potential to gain insights into the dynamics of network traffic that existing tools do not offer.