Study of video traffic In telecommunication systems for the purpose of service quality

The self-similar network traffic can have a detrimental impact on network performance, including amplified queuing delay, retransmission rate and packet loss rate. Modern network traffic consists of more bursts than Poisson models predict over many time scales. This difference has implications for performance. The video traffic research is important because self-similar nature of network traffic leads to a number of undesirable effects like high buffer overflow rates, large delays and persistent periods of congestion and the severity of these conditions is directly proportional to the degree of self-similarity. On the other hand, the long memory property of self-similar traffic is able to help to forecast traffic for the purpose of quality of service (QoS) provision. This work presents the results of the analysis of video traffic performed and study the structure of the video traffic to identify its characteristic features.