H. Che and S.-Q. Li, "Fast algorithms for measurement-based traffic modeling," IEEE Journal on Selected Areas in Communications, vol. 16, June 1998. Home/Search Document Details and Download
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On Modeling Round-Trip Time Dynamics of the Internet.. - Ohsaki, Morita, Murata (2002) (Correct)
....measurementbased studies is regarding a black box modeling of the network traffic [11 15] In [11] the authors have proposed a traffic model for wide area TCP traffic by characterizing several distributions of, for example, the packet inter arrival time and the number of bytes transferred. In [12], the authors have proposed a fast algorithm to construct a CMRP (Circulant Modulated Rate Process) for traffic modeling. In [13] CMRP and ARMA (Auto Regressive Moving Average) have been discussed as a traffic model. In [14, 15] a measurement based tool for traffic modeling and queueing analysis ....
H. Che and S.-Q. Li, "Fast algorithms for measurement-based traffic modeling," IEEE Journal on Selected Areas in Communications, vol. 16, pp. 612--625, June 1998.
Stochastic system identification for ATM network traffic models - De Cock, De Moor (1998) (1 citation) (Correct)
....where the parameters of a well chosen model class are determined from measurements of the aggregate traffic stream only. This is called the identification of a traffic model which is the main topic of this paper. Whereas the identification approach of Li and Hwang (1993a, 1993b, 1997) and of Che and Li (1998) is mainly based on the frequency domain, this paper is concerned with measurement based parameter estimation in the time domain: the models match the cumulative distribution function and the autocorrelation function of the measured data as described by Yi and De Moor (1996) The role of ....
Che H. and Li S.Q. (1998) Fast algorithms for measurement-based traffic modeling 2 . Accepted for publication in IEEE Journal on Selected Areas in Communications 16(5).
Probabilistic Burstiness-Curve-Based Connection Control for.. - Chong, Li (1997) (2 citations) Self-citation (Li) (Correct)
....approach proposed by Li in [20] The construction of an state CMPP is much simpler than that of a general state MMPP since fewer parameters need to be determined due to the cyclic repetition of transition rates. Recent development of a faster algorithm for this CMPP modeling is reported in [26]. Once a CMPP model is obtained, the next step is to compute PBC by solving a single queue, single server WCS fed by the Markovian model. This queueing system, the MMPP M 1 K queue, can be modeled by a quasi birth death (QBD) process (a) b) Fig. 3. a) DBC of MPEG JPEG video. b) End to end ....
....involved in the statistical matching and evaluation of the PBC prohibits the approach from being applied to real time situations. Note that we are not proposing an on line measurement based connection control. In other words, we collect sufficient statistics to derive the PBC. Refer to [20] and [26] for the complexity of the matching procedure, and to [22] for the complexity of PBC computation. More examples of the CMPP modeling with longer video sequences and other values of buffer capacity (other than 1000 cells) can be found in [20] 26] and [27] C. Voice Traffic A two state MMPP, ....
[Article contains additional citation context not shown here]
H. Che and S. Q. Li, "Fast algorithms for measurement-based traffic modeling," in Proc. 34th Annu. Conf. Commun., Contr. Computing, Oct. 1996 (also available at http://mocha.ece.utexas.edu/ sanqi).
Capturing Important Statistics of a Fading/Shadowing Channel for.. - Kim, Li (1999) (6 citations) Self-citation (Li) (Correct)
....may represent the number of packet arrivals at the time interval [t; t Delta) Most queueing analyses of multimedia traffic so far have focused on wireline networks such as ATM, where the service rate is assumed to be constant. Under the assumption of a constant service rate, the studies in [13, 14, 15] indicate that only the first and second order statistics of the arrival process are important to steady state queue length and loss rate solutions, whereas its higher order statistics can be neglected, given a properly selected frequency range for the measurement. Most importantly, the queueing ....
....have their energy highly concentrate on low frequency band, which is attributed to the long range dependence or large time varying scale of packet arrivals. Fig. 7 shows such examples as collected from typical Ethernet data trace and JPEG video trace. One can use the techniques developed in [13, 15] to build a Markov chain modulated process to match such statistics. For simplicity, here we assume that the data arrival process consists of M i.i.d. sources, each of which may represent a virtual connection on the channel. In this study we take M = 5. Each data 9 0 5 10 0 2 4 6 8 radian ....
[Article contains additional citation context not shown here]
Hao. Che and S.Q. Li, "Fast Algorithms for Measurement-Based Traffic Modeling," Proc. IEEE Infocom'97, Apr. 1997, pp. 53-65; also to appear in a special issue of IEEE JSAC on traffic modeling.
Modeling Multipath Fading Channel Dynamics for Packet Data.. - Kim, Li (1999) (4 citations) Self-citation (Li) (Correct)
....may represent the number of packet arrivals at the time interval [t; t Delta) Most queueing analyses of multimedia traffic so far have focused on wireline networks such as ATM, where the service rate is assumed to be constant. Under the assumption of a constant service rate, the studies in [9, 10, 11] indicate that only the first and second order statistics of the arrival process are important to steady state queue length and loss rate solutions, whereas its higher order statistics can be neglected, given a properly selected frequency range for the measurement. Most importantly, the queueing ....
....have their energy highly concentrated on a low frequency band, which is attributed to the long range dependence or large time varying scale of packet arrivals. Fig. 5 shows such examples collected from a typical Ethernet data trace and JPEG video trace. One can use the techniques developed in [9, 11] to build a Markov chain modulated process to match both first and second order statistics which are important to queueing analysis. For simplicity, here we assume that the data arrival process consists of M i.i.d. sources, each of which may represent a virtual connection on the channel. In this ....
[Article contains additional citation context not shown here]
Hao. Che and S.Q. Li, "Fast Algorithms for Measurement-Based Traffic Modeling," Proc. IEEE Infocom'97, Apr. 1997, pp. 53-65.
Modeling End-to-End Packet Delay Dynamics of the Internet - Using System Identification (2000) (Correct)
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H. Che and S.-Q. Li, "Fast algorithms for measurement-based traffic modeling," IEEE Journal on Selected Areas in Communications, vol. 16, June 1998.
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