Will E. Leland et al. "On the Self-Similar Nature of Ethernet Tra#c (Extended Version)",IEEE/ACM Trans. on Networking, vol.2, no.1, Feb 1994, pp. 1-15  Home/Search   Document Not in Database   Summary   Related Articles   Check

....algebra. This might lead to exponential bounds under the G artner Ellis large deviation conditions [18, 16] for arrival times and service requirements. For Markov processes, it is expected that one might only need g servers with g being linear. However, for long range dependent inputs (see e.g. [22]) additional service e orts are required and one might need nonlinear g servers as discussed in [15, 7, 8] iii) Dynamic service guarantees: as discussed in Section 3.1, our trac characterization is shift invariant. This can be relaxed by considering the following dynamic trac characterization ....

W.E. Leland, M.S. Taqqu, W. Willinger, D. V. Wilson, "On the Self-Similar Nature of Ethernet Trac (Extended Version),"IEEE/ACM Transactions on Networking, Vol. 2, No. 1, Feb. 1994.

....parameters and time scales. Numerical examples show that the loss probability of MMPP D 1 K are not significantly a#ected by the time scale. 1 Introduction The long range dependency (LRD) and the self similar process have been greatly concerned with the high speed computer communication networks [2, 4]. The self similar process is quite di#erent from traditional tra#c models such as Poisson process and Markovian arrival process (MAP ) This observation has initiated studies of new models such as chaotic maps, fractional Brownian motion (FBM) and fractional autoregressive integrated moving ....

W. Leland, M. Taqqu, W. Willinger and D. Wilson, "On the Self-Similar Nature of Ethernet Tra#c (Extended Version)," IEEE/ACM Trans. Networking, vol. 2, no. 1, pp.1-15, 1994.

....of multimedia tra#c in high speed networks such as packet streams in local area networks (LAN) cell streams from variable bit rate (VBR) video streams in ATM networks, etc. have been carried out and analyzed. They have shown that the tra#c from those networks appears to be self similar [4,12]. The self similar tra#c is characterized by that the correlation never vanishes in a large time scale. Its tra#c looks the same regardless of time scales over a long range interval. This fractal behavior makes the tra#c very bursty. These properties of the self similar tra#c are quite di#erent ....

....of arrival time whose time scale is up to 10 . Samples 1, 2 and 3 were generated changing H = 0.6, 0.7 and 0.8, respectively, with # = 1.0 and # = 0.6. Then we estimated mean arrival rate #, and Hurst parameter H for each sequence using aggregated variance method (for details, see [12] and references therein) The results of estimation are presented in Table 3. In Figures 3 and 4, we show the variance time curves of the MMPPs obtained from Sample 2 according to our fitting method. In both figure, dotted lines illustrate the variance curves of resulting MMPPs and solid lines ....

W. Leland, M. Taqqu, W. Willinger and D. Wilson, "On the Self-Similar Nature of Ethernet Tra#c (Extended Version)," IEEE/ACM Transactions on Networking, vol. 2, no. 1, pp.1-15, 1994.

....strong correlations on the time scale of few hundred seconds may be human think time and human distractedness. The overall self similarity, at least asymptotically, may be argued for by invoking the well known on o# process that was crucial in explaining selfsimilarity in network tra#c loads [13]: The number of requests per session follows a heavy tailed distribution. Since the number of requests sent per time unit is limited, sessions are thus sending requests over on times that are heavytailed. Numerical support for this claim comes from our analysis of session duration in Sec. 6, which ....

W. Leland, M. Taqqu, W. Willinger, and D. Wilson, "On the self-similar nature of Ethernet tra#c (extended version)," IEEE/ACM Trans. Networking, pp. 1-- 15, 1994.

....this tutorial paper, we focus on two such invariants related to the time dimension of the problem, namely, long range dependence, or selfsimilarity, and heavy tail marginal distributions. Both characteristics arise in most scalar signals that can be extracted from complete network traffic traces [27, 35, 3, 43]. Typical scalar signals include continuous time point processes constructed from recording the arrival times of successive IP (Internet Protocol) packets at some point of the network, or a time series obtained by counting the size of the data transferred during some time intervals. In order to ....

....bursty in the bottom plot despite the fact that each point in it is obtained as the sum of one thousand successive values of the series displayed in the top plot of figure 1. Similar characteristics have been observed in many di#erent experimental setups, including both LAN and WAN data (e.g. [27, 35, 3] and the references therein) 10 0 10 1 10 2 10 3 10 7 10 8 frame size inter frames variance normalized by frame size (logscale) Figure 2: Variance time plot: Empirical variance of the aggregated process normalized by the size of the aggregation frame, plotted as a function of the size of ....

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W.E. Leland, M.S. Taqqu, W. Willinger and D.V. Wilson, "On the self-similar nature of Ethernet tra#c (extended version) ," IEEE/ACm Trans. Networking, vol. 2, pp. 103-115, 1994.

....Categories and Subject Descriptors C.2.2 [Computer Communication Networks] Network Protocols General Terms Measurement Keywords Network measurement, TCP, flow rates 1. INTRODUCTION Researchers have investigated many aspects of Internet tra#c, including characteristics of aggregate tra#c [8, 16], the sizes of files transferred, tra#c of particular applications [4] and routing stability [7, 17] to name a few. One area that has received comparatively little attention is the rate at which applications or flows transmit data in the Internet. This rate can be a#ected by any of a number of ....

W. Leland, M. Taqqu, W. Willinger, and D. Wilson, "On the Self-Similar Nature of Ethernet Tra#c (Extended Version)," IEEE/ACM Transaction on Networking , 2(1), pp. 1-15, Feb. 1994.

....to using only a narrow bandwidth. key words: ######### ################ ###### ######### #### ##### ##### ###### ###### ############# ######## 1. Introduction It has beenrep orted that teletra#c over a wired network such as the Internet or local area networks has a self similar characteristic [1] [3] There are also rep orts that self similarityap ears even in the teletra#c of cellular communication networks because of the hierarchical structure of cellular systems [4] and because of the heavy tailed distribution of holding time [5] This fact has drawn much attention because ....

W.E. Leland, M.S. Taqqu, W. Willinger, and D.V. Wilson, "On the self-similar nature of ethernettra#c (extended version) ," IEEE/ACM Trans. Networking, vol.2, no.1, pp.1-- 15, Feb. 1994.

....amount of simulation needed to determine the cell blocking probability at the switch, which would speed up the simulation. We consider the network model shown in Figure 4.8. Each node contains a tra#c source and a network switch. Because actual ATM tra#c has been observed to be selfsimilar [66] [67], 68] each tra#c source is modeled by an M G # queue, where the service time has a Pareto distribution. The count process X ,t=0, 1, 2, produced by the M G # queue model, where X t represents the number of customers in the system at time t, produces an asymptotically self similar ....

W. Leland, M. Taqqu, W. Willinger, and D. Wilson, "On the self-similar nature of ethernet tra#c (extended version)," IEEE/ACM Transactions on Networking, vol. 2, pp. 1--15, February 1994.

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Will E. Leland et al. "On the Self-Similar Nature of Ethernet Tra#c (Extended Version)",IEEE/ACM Trans. on Networking, vol.2, no.1, Feb 1994, pp. 1-15

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W. Leland, M. Taqqu, W. Willinger, and D. Wilson, "On the self-similar nature of Ethernet tra#c (extended version) ," Networking, IEEE/ACM Transactions on, Volume: 2 Issue: 1 , Feb. 1994 Page(s): 1-15.

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W. Leland, M. Taqqu, W. Willinger, and D. Wilson, "On the self-similar nature of ethernet tra#c (extended version)," IEEE/ACM Transactions on Networking 2, pp. 1--15, February 1994.

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W. Leland, M. Taqqu, W. Willinger, and D. Wilson, "On the self-similar nature of ethernet tra#c (extended version)," IEEE/ACM Trans. Networking, 1994.

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W.E. Leland, M.S. Taqqu, W. Willinger, and D.V. Wilson, "On the self-similar nature of Ethernet tra#c (extended version)", IEEE/ACM Transactions on Networking, Vol.2:103-115, 1994.

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Leland, W.E.; Taqqu, M.S.; Willinger, and D.V. W.; Wilson, "On the self-similar nature of Ethernet tra#c (extended version)," ACM/IEEE Transactions on Networking, vol. 2, no. 1, pp. 1--15, Feb. 1994.

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