Web Conferencing Traffic - An Analysis using DimDim as Example

In this paper, we present an evaluation of the Ethernet traffic for host and attendees of the popular opensource web conferencing system DimDim. While traditional Internet-centric approaches such as the MBONE have been used over the past decades, current trends for web-based conference systems make exclusive use of application-layer multicast. To allow for network dimensioning and QoS provisioning, an understanding of the underlying traffic characteristics is required. We find in our exemplary evaluations that the host of a web conference session produces a large amount of Ethernet traffic, largely due to the required control of the conference session, that is heavily-tailed distributed and exhibits additionally long-range dependence. For different groups of activities within a web conference session, we find distinctive characteristics of the generated traffic

Video Traffic Characteristics of Modern Encoding Standards: H.264/AVC with SVC and MVC Extensions and H.265/HEVC

Video encoding for multimedia services over communication networks has significantly advanced in recent years with the development of the highly efficient and flexible H.264/AVC video coding standard and its SVC extension. The emerging H.265/HEVC video coding standard as well as 3D video coding further advance video coding for multimedia communications. This paper first gives an overview of these new video coding standards and then examines their implications for multimedia communications by studying the traffic characteristics of long videos encoded with the new coding standards. We review video coding advances from MPEG-2 and MPEG-4 Part 2 to H.264/AVC and its SVC and MVC extensions as well as H.265/HEVC. For single-layer (nonscalable) video, we compare H.265/HEVC and H.264/AVC in terms of video traffic and statistical multiplexing characteristics. Our study is the first to examine the H.265/HEVC traffic variability for long videos. We also illustrate the video traffic characteristics and statistical multiplexing of scalable video encoded with the SVC extension of H.264/AVC as well as 3D video encoded with the MVC extension of H.264/AVC

Prediction of RoHCv1 and RoHCv2 compressor utilities for VoIP

Modern cellular networks utilising the long–term evolution (LTE) and the coming 5G set of standards face an ever–increasing demand for low–latency mobile data from connected devices. Header compression is employed to minimise the overhead for IP–based cellular network traffic, thereby decreasing the overall bandwidth usage and, subsequently, transmission delays. Here, we employ machine learning approaches for the prediction of Robust Header Compression version 1’s and version 2’s compression utility for VoIP transmissions, which allows the compression to dynamically adapt to varying channel conditions. We evaluate various regression models employing r2 and mean square error scores next to complexity (number of coefficients) based on an RTP specific training data set and separately captured live VoIP audio calls. We find that the proposed weighted Ridge regression model explains about at least 50 % of the observed results and the accuracy score may be as high as 94 % for some of the VoIP transmissions