nformation, ultimately increasing the bitrate and further loading the network elements. Error concealment by the application is the preferred method for video because it results in no overhead. Packet loss is often modeled using simple models, and while incapable of modeling the self-similarity of the traffic in the Internet, these models are often fit for purpose. Multicast UDP packet losses have been successfully modeled (Clark & Fang, 1998; Bolot et al., 1995) Chapter 3 Digital Video Transmission Fig. 3.21 Consecutive packet loss between eagle.essex.ac.uk Loss Duration (packets) and bmrc.berkeley.edu. "Berk4pmLoss" 0.024 0.976 Nightime 0.064 0.936 Fig. 3.22 Packet loss modeling Daytime using a two-stage Gilbert model. 1 = Packet loss 0 = Packet received using a simple two-stage Gilbert loss model, shown in Figure 3.22. The statistics for the model were obtained using 384,000 packets transmitted over a 24-hour period. You will note considerable variations in delivery probability according to the time of day. On the Internet, delays are highly variable. Figure 3.23 shows a typical round-trip delay between eagle.essex.ac.uk and bmrc.berkeley.edu at 4 p.m. GMT on a weekday. The playout instant for media must strike a compromise between delay and interactivity when dealing with round-trip variations. Shorter delays introduce higher losses, as delayed packets are assumed to have been lost; longer delays reduce the interactivity and increase the buffering requirements. Countering Loss Effects Fig. 3.23 Interarrival times or jitter between eagle.essex_ac_uk Round-trip Delay (ms) and bmrc.berkeley.edu. "Berk4pmJitter" Self-Similarity of Traffic Published work (SIGMETRICS, 1996) has shown that Internet loss statistics are fractal in nature and that packet loss profiles possess self-similarity when examined across different lengths of time. Knowledge of such behavior is useful in predicting loss statistics and has been highlighted here to encourage the reader to investigate further, but it remains outside the scope of th