B. Ryu and S.B. Loven, Point Process Approaches for Modeling and Analysis of Self--Similar Traffic: Part II---Applications. In Proc. 5th Int'l Conf. Telecommunications Systems, Modeling, and Analysis. Nashville, TN, March 1997. Home/Search Document Details and Download
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Multifractal Analysis and Modeling of Long-Range-Dependent Traffic - Gao, Rubin (1999) (2 citations) (Correct)
....the basic LRD property of traffic processes. Such approaches include chaotic maps [5] a LRD ON OFF model [18] Cox s M G 1 type models [4,8,11,17] the Fractional Brownian motion (FBm) model [9,10] fractional autoregressive integrated moving average (FARIMA) models [7,15] point processes [14], and pseudo models [1,13] An issue of much interest is whether and how multifractal can be employed to model LRD traffic. Recently Taqqu et al. 16] have analyzed aggregated network traffic processes using the multifractal concept. They conclude that when selfsimilar traffic models can be ....
B. Ryu and S.B. Loven, Point Process Approaches for Modeling and Analysis of Self--Similar Traffic: Part II---Applications. In Proc. 5th Int'l Conf. Telecommunications Systems, Modeling, and Analysis. Nashville, TN, March 1997.
Multifractal Modeling of Counting Processes of Long-Range.. - Gao, Rubin (1999) (5 citations) (Correct)
....the basic LRD property of traffic processes. Such approaches include chaotic maps [5] a LRD ON OFF model [20] Cox s M G 1 type models [4,10,13,19] the Fractional Brownian motion (FBm) model [11,12] fractional autoregressive integrated moving average (FARIMA) models [9,17] point processes [16], and pseudo models [1,15] An issue of much interest is whether and how multifractal can be employed to model LRD traffic. Using Bellcore s LAN and WAN traffic trace data, we have found [7] that the interarrival time series and the packet length sequences are long range dependent, and are ....
B. Ryu and S.B. Loven, Point Process Approaches for Modeling and Analysis of Self--Similar Traffic: Part II---Applications. In Proc. 5th Int'l Conf. Telecommunications Systems, Modeling, and Analysis. Nashville, TN, March 1997.
The Relevance of Short-Range and Long-Range Dependence of VBR.. - Ryu, Elwalid (1997) (1 citation) Self-citation (Ryu) (Correct)
....the Gaussian distribution is obtained as M 1, however, realistic numbers are often sufficient for practical purposes. For example, M = 10 shows a fairly good approximation, with a skewness of zero and a kurtosis 2. 8; corresponding values for an exactly Gaussian process are zero and 3 [15, 20]. SRD (Markov process) and is a special case of DAR(p) presented in Section 3.3, contributes to geometric decay for small lags and the FBNDP contributes to power law decay for large lags. This construction method permits full control of both the short term and long term correlations, and ....
B. Ryu and S. Lowen. Point process approaches for modeling and analysis of self-similar traffic: Part ii -- applications. In Proc. 5th Int'l Conf. on Telecommunications Systems, Modeling, and Analysis, Nashville, TN, 1997.
Fractal Network Traffic Modeling: Past, Present, and Future - Ryu Self-citation (Ryu) (Correct)
....the area of fractal network traffic modeling and analysis. By doing so, we hope to provide a unified approach to the understanding of the role and implications of fractal behavior in traffic engineering for emerging networks such as B ISDN and Integrated Services Internet. 2 Past As discussed in [25], we find it much easier to understand the recent results on the impact of fractal characteristics of network traffic on traffic engineering if we divide fractal behavior into two types: isolated fractal behavior and interaction induced fractal behavior. A traffic source exhibits isolated fractal ....
....each connection. They employ so called the nested factors to quantitatively determine which factors contribute to the Hurst parameter, and conclude that the heavy tailed joint distribution of TCP connection volumes (sizes) and connection transmission rates are the key factors. Ryu and Lowen [25] employ the Fractal Shot Noise Driven Poisson Point Process (FSNDP) to explain the fractal behavior of TCP traffic. The FSNDP model, one of many fractal modulated Poisson processes constructed and analyzed in [26] consists of the first stage homogeneous Poisson process dM(t) and the second stage ....
B. Ryu and S. Lowen. Point process approaches for modeling and analysis of selfsimilar traffic: Part ii -- applications. In Proc. 5th Int'l Conf. on Telecommunications Systems, Modeling, and Analysis, Nashville, TN, 1997.
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