<abstract xml:lang="en" xmlns="http://www.w3.org/1999/xhtml"><p>Video services became a large part of internet network traffic. Therefore understanding of video coding standards and video traffic sources, such as video trace files is highly important. In this paper we concentrate on the basic characteristics of mpeg-4 and h.264 video coding standards. We describe the concept of the <italic>i</italic>, <italic>p</italic> and <italic>b</italic> frames in these standards since they are the main feature of every video trace file. Then we describe the content of the video trace files since the trace files are important for researchers to investigate network performance and understanding of network features. These are the important issues in terms of assuring the quality of service (QoS) in multimedia applications spread across the internet. Traffic prediction and bandwidth allocation are the crucial parts in terms of QoS. In this kind of applications, the artificial neural networks are vastly used. Therefore we illustrate the results of neural networks for video traffic prediction using both mpeg-4 and h.264 trace files.</p></abstract>

Video services became a large part of internet network traffic. Therefore understanding of video coding standards and video traffic sources, such as video trace files is highly important. In this paper we concentrate on the basic characteristics of mpeg-4 and h.264 video coding standards. We describe the concept of the i, p and b frames in these standards since they are the main feature of every video trace file. Then we describe the content of the video trace files since the trace files are important for researchers to investigate network performance and understanding of network features. These are the important issues in terms of assuring the quality of service (QoS) in multimedia applications spread across the internet. Traffic prediction and bandwidth allocation are the crucial parts in terms of QoS. In this kind of applications, the artificial neural networks are vastly used. Therefore we illustrate the results of neural networks for video traffic prediction using both mpeg-4 and h.264 trace files.

Prediction Methods for MPEG-4 and H.264 Video Transmission

Faculty of Electrical Engineering and Information Technology, Department of Applied Informatics and Information Technology, Slovak University of Technology in Bratislava, Slovakia

Journal of Electrical Engineering

{"article-title":"Prediction Methods for MPEG-4 and H.264 Video Transmission"}

Video services became a large part of internet network traffic. Therefore understanding of video coding standards and video traffic sources, such as video...

Prediction Methods for MPEG-4 and H.264 Video Transmission

Publicado en línea: 07 jun 2011

Páginas: 57 - 64

DOI: https://doi.org/10.2478/v10187-011-0010-6

Palabras clave
video encoding, coding standards, prediction, neural networks

This content is open access.

Prediction Methods for MPEG-4 and H.264 Video Transmission

Publicado en línea: 07 jun 2011

Páginas: 57 - 64

DOI: https://doi.org/10.2478/v10187-011-0010-6

Palabras clavevideo encoding, coding standards, prediction, neural networks

This content is open access.

Palabras clave
video encoding, coding standards, prediction, neural networks