Wavelet-Based Estimation of Long-Range Dependence in MPEG Video Traces

Cackov, N.; Lucic, Z.; Bogdanov, Momcilo; Trajković, Ljiljana

doi:10.1109/iscas.2005.1465025

Cited by 14 publications

(13 citation statements)

References 8 publications

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“…Within the scope of this study, the validity of the Poisson process assumption used in classical communication systems to model arrival process will be investigated by evaluating the correlation between voice calls (composed of incoming and outgoing calls) in the time domain. In this direction, Hurst parameter estimation methods, commonly used in self‐similar and long range dependent traffic analyses, will be used . There are various methods used to estimate the Hurst parameter; the most common ones are the modified Allan variance (MAVAR) and wavelet log‐scale diagram methods .…”

Section: Arrival Processmentioning

confidence: 99%

“…Let x ( t ) represent a random process called fractional noise (or power law). The autocorrelation function of x ( t ) can be defined as

R (τ) MathClass-rel= c_{r} MathClass-rel| τ {MathClass-rel|}^{MathClass-bin- (1 MathClass-bin- α)} MathClass-punc, τ MathClass-rel\to MathClass-rel\infty

where c r is a positive constant and α is the spectral or scaling exponent ( α ∈ (0,1)).…”

Section: Arrival Processmentioning

confidence: 99%

“…In order to show that calls are completely independent from each other and that call arrival process can be modeled with Poisson distribution in cellular networks, the Hurst parameter value should be H = 1 ∕ 2. Through the analysis presented earlier, this is equivalent to μ ≅ − 3 or α ≅ 0 . In this case, PSD of random process x ( t ) will be a fixed value in all frequencies and should be proper to PSD of the white noise.…”

Section: Arrival Processmentioning

confidence: 99%

See 2 more Smart Citations

User behavior modeling of voice communications: an empirical study

Büyükçorak

Kurt

Toprakkiran

2014

Wireless Communications

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In this study, analysis and modeling of arrival and service processes are presented in a comprehensive fashion in order to determine statistical properties of voice traffic from end-user perspective in accordance with the queueing theory. For the first time in the literature, we introduce a user centric approach and examine these services considering both flow directions of voice traffic, the uplink and the downlink as opposed to existing studies with the network centric approach. In our study, we use experimental data composed of actual phone calls collected from 2G/3G networks. To achieve this, we designed and implemented a data collection system for mobile users and compared the results by using data from an operational cellular network. In order to determine the time correlation of voice calls, Hurst parameter estimation methods are used. On the basis of the outcomes, independency of call arrivals is shown. Additionally, it is shown that calls acquired from user and network centric approaches are both Poisson distributed. Next, looking at the problem from service process perspective, thorough analyses are performed to determine mathematical models that can best characterize call holding times. Maximum likelihood estimation and expectation maximization algorithm are used, and it is shown that the optimum mathematical model for the characterization of call holding times is the lognormal distribution family.

show abstract

Section: Arrival Processmentioning

confidence: 99%

“…Let x ( t ) represent a random process called fractional noise (or power law). The autocorrelation function of x ( t ) can be defined as

R (τ) MathClass-rel= c_{r} MathClass-rel| τ {MathClass-rel|}^{MathClass-bin- (1 MathClass-bin- α)} MathClass-punc, τ MathClass-rel\to MathClass-rel\infty

where c r is a positive constant and α is the spectral or scaling exponent ( α ∈ (0,1)).…”

Section: Arrival Processmentioning

confidence: 99%

Section: Arrival Processmentioning

confidence: 99%

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User behavior modeling of voice communications: an empirical study

Büyükçorak

Kurt

Toprakkiran

2014

Wireless Communications

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“…The details of using wavelets in Hurst parameter estimation is given in [7]. The estimator we used is a multifractal estimator which takes into account moments of higher order given as…”

Section: Hurst Parameter Estimationmentioning

confidence: 99%

Performance of distribution networks under VBR video traffic

Özdem

Erten

2007

Proceedings 2007 IEEE SoutheastCon

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In this study we tested the average delay and packet loss performance of access networks under variable bit rate (VBR) video traffic. We used ns-2 simulator to perform the simulations, and actual as well as synthetically generated ON/OFF sources with ON and OFF times taken from exponential or Pareto distributions are used as inputs to the simulated networks. To make sure that the synthetic sources have vbr-video like characteristics we chose the parameters of these sources such that their Hurst parameter is as close to 1 as possible. We then tested the performance of a network when data produced by these sources is applied as input. The results show that both actual and synthetic sources produce similar results and that the access networks should have at least 1 Mbps speeds to support acceptable quality video transmission.

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“…In some circumstances, some traffic is more complicated than self-similarity, which behaves as multifractal [6] [7]. Based on the theory of wavelet and fractal, some traffic models are studied in [8] [9]. This paper introduces a novel traffic model, that is very accurate and robust in traffic simulation.…”

Section: Introductionmentioning

confidence: 99%

A Network Traffic Model Based on Fractal

Xu¹

2007

2007 International Conference on Wireless Communications, Networking and Mobile Computing

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The study on the model of traffic flow is one of the research hotshots in computer network. Employing fractal theory, we set up a mathematical model of traffic flow whose properties depending on the parameters like the ratio distribution of the traffic flow and corresponding time intervals. The self-similar or multifractal traffic can be simulated when the parameters are in different certain ranges. Furthermore, some numerical experiments are shown in this paper to verify the effectiveness of the traffic mathematical model.

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Wavelet-Based Estimation of Long-Range Dependence in MPEG Video Traces

Cited by 14 publications

References 8 publications

User behavior modeling of voice communications: an empirical study

User behavior modeling of voice communications: an empirical study

Performance of distribution networks under VBR video traffic

A Network Traffic Model Based on Fractal

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