Ten lectures on wavelets
On the self-similar nature of Ethernet traffic (extended version)
IEEE/ACM Transactions on Networking (TON)
Measurement-based admission control with aggregate traffic envelopes
IEEE/ACM Transactions on Networking (TON)
Connection-level analysis and modeling of network traffic
IMW '01 Proceedings of the 1st ACM SIGCOMM Workshop on Internet Measurement
Testing the Gaussian approximation of aggregate traffic
Proceedings of the 2nd ACM SIGCOMM Workshop on Internet measurment
A wavelet-based joint estimator of the parameters of long-range dependence
IEEE Transactions on Information Theory
Statistical service assurances for traffic scheduling algorithms
IEEE Journal on Selected Areas in Communications
A distribution-based approach to anomaly detection and application to 3G mobile traffic
GLOBECOM'09 Proceedings of the 28th IEEE conference on Global telecommunications
Distribution-based anomaly detection in 3G mobile networks: from theory to practice
International Journal of Network Management
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In this paper we propose a method for the analysis of aggregate traffic by means of empirical rate-interval curves obtained from experimental data. The approach is related to the theory of Network Calculus, and is based on an algorithm which is different from the commonly employed approach based on wavelets, although it retains some of its multiresolution features. We present results, obtained both by simulation and in the analysis of real traffic traces, which provide an assessment of the strengths and weaknesses of the proposed method. Rate-interval curve analysis provides very robust and acceptably accurate estimates of the Hurst parameter value and, even in the presence of flow irregularities, results can be proved to be correct as far as scaling properties are concerned. Further analyses concerning peaks, bursts and similar localized phenomena that may have a significant impact on the performances of a network are allowed by considering maximal rate envelopes.