M. R. Ismail, I. Lambdaris, M. Devetsikiotis, and A. R. Kaye, "Modeling prioritized MPEG video using tes and a frame spreading strategy for transmission in ATM networks," in Proc. IEEE INFOCOM'95, Apr. 1995, pp. 762--769.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....durations) D. Second Order Statistics Based Modeling A common approach to modeling video streams is to generate a stochastic process that matches its first and second order statistics, i.e. its marginal distribution and autocorrelation functions (ACF s) see, for example, 22] 3] 4] [23]) For these methods to work well, it is desirable to have an easily computable expression of the ACF for the generated process Fig. 4. Multiple time scale model of MPEG video. in terms of model parameters. For the model presented in Section II C above, we obtain such expressions after some ....

M. R. Ismail, I. Lambdaris, M. Devetsikiotis, and A. R. Kaye, "Modeling prioritized MPEG video using tes and a frame spreading strategy for transmission in ATM networks," in Proc. IEEE INFOCOM'95, Apr. 1995, pp. 762--769.

.... measures based on frame rate and frame size, we have studied the quality of service for MPEG video in human perspective [31] There are also extensive studies on MPEG video characterization and modeling by Ismail, Lambadaris, and Devetsikiotis, Izquierdo and Reeves, and Krunz, Sass, and Hughes [10 12]. For the quality of service support, various QoS control mechanisms have been proposed. While Bolot and Turletti proposed a rate control mechanism for transmitting packet video over the Internet [34] Reibman et al. [24,35] and Reininger et al. [25] made use of an adaptive congestion control ....

M. Ismail, I Lambadaris, and Devetsikiotis, "Modeling Prioritized MPEG Video Using TES and Frame Spreading Strategy for Transmission in ATM Networks", Proc. IEEE INFOCOM, April 1995.

....not only capture the marginal distribution of the frame sizes, but also more importantly the characteristics of the autocorrelation function. TES is a convenient tool capable of doing both simultaneously. 6] and [10] studied TES modeling of variable bit rate (VBR) compressed video trac. 12] and [3] studied a composite TES model for MPEG coded video trac. 9] studied a Markov Renewal Modulated TES model for modeling a full length JPEG video trac trace. E ective bandwidth is a trac descriptor, which characterizes how much bandwidth should be allocated to an input trac process in order to ....

....TES with a Markovchain innovation sequence can be done in a similar but more complicated way, and will be presented in future works. Let #Z # : n =0;1;2;#### denote a TES # process. This process can represent a sequence of video frame sizes for video trac modeling (for example, 6] 12] [3], and [9] Using similar notations of [7] Z # = D(U # # ) D(#) F ## # (S # (#) U # # = # # # # # # # # # U # ; n =0; U # ### V # ; n # 1: F# (#) is the marginal probability distribution function of Z # , # is the modulo 1 operator # , and S # (#) is a stitching ....

Ismail, M. R., Lambadaris, I. E., Devetsikiotis, M., and Kaye, A. R. (1995), \Modeling Prioritized MPEG Video Using TES and a Frame Spreading Strategy for Transmission in ATM Networks", ########### ## #### ##########, Boston, Massachusetts, pp.762-770. ##### ########### ######## ########## ### ### ######### 22

....the multiple time scale model 5.2. 4 Second Order Statistics Based Modeling A common approach to modeling of VBR video streams is to generate a stochastic process that matches first and second order statistics, i.e. its marginal distribution and auto correlation functions (ACF) see for example [84, 77, 76, 56]) For these methods to work well it is desirable to have an easily computable expression of the ACF of the generated process in terms of model parameters. For the model presented in Section 5.2.3 above, we obtain such expressions after some simplifying assumptions, and show how a simple model ....

M. R. Ismail, I. Lambdaris, M. Devetsikiotis, and A. R. Kaye. Modeling prioritized MPEG video using tes and a frame spreading strategy for transmission in ATM networks. In Proc. IEEE Infocomm., pages 762--769, April 1995.

....to CBR coding and it can lead to variations in image quality in a sequence. In [6] a leaky bucket controller is applied to shape the VBR video signal in order to control cell loss rate. Some studies have used TES modeled video to investigate the performance of multiplexed video signals [7] In [8] a frame spreading strategy is used to reduce the variability of bit rate. In order to achieve a higher multiplexing gain, traffic shaping mechanisms generally impose a delay according to a fixed algorithm which can be in the order of a frame time. Besides, to achieve a high throughput with an ....

M.R. Ismail, I.E. Lambadavis, M. Devetsikiotis, and A.R. Kaye," Modeling prioritized MPEG video using TES and a frame spreading strategy for transmission in ATM networks,"IEEE INFOCOM'95, pp 762-770

.... measures based on frame rate and frame size, we have studied the quality of service for MPEG video in human perspective [31] There are also extensive studies on MPEG video characterization and modeling by Ismail, Lambadaris, and Devetsikiotis, Izquierdo and Reeves, and Krunz, Sass, and Hughes [10 12]. For the quality of service support, various QoS control mechanisms have been proposed. While Bolot and Turletti proposed a rate control mechanism for transmitting packet video over the Internet [34] Reibman et al. [24,35] and Reininger et al. [25] made use of an adaptive congestion control ....

M. Ismail, I Lambadaris, and Devetsikiotis, "Modeling Prioritized MPEG Video Using TES and Frame Spreading Strategy for Transmission in ATM Networks", Proc. IEEE INFOCOM, April 1995.

.... explicitly model the deterministic structure of MPEG video have been proposed recently, but they either do not capture any second order or time dependence properties at all (see Krunz et al. 1995) or if they do, do not accurately model the cross correlation between different frame types (see Ismail et al. 1995)) 3.1 Constructing the model If we decompose the video stream into two time scales, the GOP pattern is naturally associated with the slow time scale, via three mutually independent (but correlated) slow time scale processes corresponding to the I, P and B substreams. Indeed, I frames are coded ....

M. R. Ismail, I. Lambdaris, M. Devetsikiotis, and A. R. Kaye (1995). Modeling prioritized MPEG video using tes and a frame spreading strategy for transmission in ATM networks. In Proc. IEEE Infocomm., pages 762--769, April 1995.

....very little and only scene changes or other abrupt changes can cause rate change in the video. Theoretical descriptions of the technique can be found in Fang et al. 42] and Lambadaris [45] and references therein. An application of TES to modeling MPEG video has been provided by Ismail et al. [44], and a software modeling tool has been introduced by Geist and Melamed [43] TES models can also be used to generate traffic (Frost and Melamed [56] Neural networks have also been applied in traffic modeling in telecommunications for their ability to classify (Lippmann [15] and implement ....

M. Ismail, I. Lambadaris, M. Devetsikiotis, and A. Kaye, "Modeling prioritized MPEG video using TES and a frame spreading strategy for transmission in ATM networks", in Proc. IEEE Infocom, Boston 1995.

....on scene durations) D. Second Order Statistics Based Modeling A common approach to modeling video streams is to generate a stochastic process that matches its first and second order statistics, i.e. its marginal distribution and autocorrelation functions (ACF) see for example [22] 3] 4] [23]) For these methods to work well it is desirable to have an easily computable expression of the ACF for the generated process in terms of model parameters. For the model presented in Section II C above, we obtain such expressions after some further simplifying assumptions, and show how a simple ....

M. R. Ismail, I. Lambdaris, M. Devetsikiotis, and A. R. Kaye, "Modeling prioritized MPEG video using tes and a frame spreading strategy for transmission in ATM networks," in Proceedings of INFOCOM'95, April 1995, pp. 762--769.

....on scene durations) D. Second Order Statistics Based Modeling A common approach to modeling video streams is to generate a stochastic process that matches its first and second order statistics, i.e. its marginal distribution and autocorrelation functions (ACF) see for example [22] 3] 4] [23]) For these methods to work well it is desirable to have an easily computable expression of the ACF for the generated process in terms of model parameters. For the model presented in Section II C above, we obtain such expressions after some further simplifying assumptions, and show how a simple ....

M. R. Ismail, I. Lambdaris, M. Devetsikiotis, and A. R. Kaye, "Modeling prioritized MPEG video using tes and a frame spreading strategy for transmission in ATM networks," in Proceedings of INFOCOM'95, April 1995, pp. 762--769.

Online articles have much greater impact   More about CiteSeer.IST   Add search form to your site   Submit documents   Feedback  

CiteSeer.IST - Copyright Penn State and NEC