Add to ORKGA wavelet-based estimator for the analysis of self-similarity and long-range dependence is studied. The estimator is shown to be unbiased and highly robust against the presence of deterministic trends. The estimator is used to perform a thorough analysis of the self-similarity in Web-cache traffic, which is known to contain periodic trends due to usage patterns of Web users. Keywords
The paper elaborates the complexity and importance of modeling Internet traffic. In this sense, havi...
Recently the notion of self-similarity has been shown to apply to wide-area and local-area network t...
AbstractAs self-similarity trail is being detected in many types of traffic, and the Markovian model...
We present a method to extract a time series (Number of Active Requests (NAR)) from web cache logs w...
This article studies the problem of estimating the self-similarity parameter of network traffic trac...
We propose a novel wavelet-based approach (WBA) that accurately decides if the Internet traffic is c...
World Wide Web (WWW) traffic will dominate network traffic for the foreseeable future. Accurate pred...
Abstract—A wavelet-based tool for the analysis of long-range dependence and a related semi-parametri...
Various wavelet-based estimators of self-similarity or long-range dependence scaling exponent are st...
Abstract. We present a method to extract a time series (Number of Ac-tive Requests (NAR)) from web c...
In this paper we consider trend to be smooth deterministic changes over long scales, and tackle the ...
Recently the notion of self-similarity has been shown to apply to wide-area and local-area network t...
Introduction A self-similar process is loosely defined as a stochastic process which generates a sa...
The Hurst parameter H characterizes the degree of long-range dependence (and asymptotic self-similar...
Recently the notion of self-similarity has been shown to apply to wide-area and local-area network t...
The paper elaborates the complexity and importance of modeling Internet traffic. In this sense, havi...
Recently the notion of self-similarity has been shown to apply to wide-area and local-area network t...
AbstractAs self-similarity trail is being detected in many types of traffic, and the Markovian model...
We present a method to extract a time series (Number of Active Requests (NAR)) from web cache logs w...
This article studies the problem of estimating the self-similarity parameter of network traffic trac...
We propose a novel wavelet-based approach (WBA) that accurately decides if the Internet traffic is c...
World Wide Web (WWW) traffic will dominate network traffic for the foreseeable future. Accurate pred...
Abstract—A wavelet-based tool for the analysis of long-range dependence and a related semi-parametri...
Various wavelet-based estimators of self-similarity or long-range dependence scaling exponent are st...
Abstract. We present a method to extract a time series (Number of Ac-tive Requests (NAR)) from web c...
In this paper we consider trend to be smooth deterministic changes over long scales, and tackle the ...
Recently the notion of self-similarity has been shown to apply to wide-area and local-area network t...
Introduction A self-similar process is loosely defined as a stochastic process which generates a sa...
The Hurst parameter H characterizes the degree of long-range dependence (and asymptotic self-similar...
Recently the notion of self-similarity has been shown to apply to wide-area and local-area network t...
The paper elaborates the complexity and importance of modeling Internet traffic. In this sense, havi...
Recently the notion of self-similarity has been shown to apply to wide-area and local-area network t...
AbstractAs self-similarity trail is being detected in many types of traffic, and the Markovian model...