Delivery of real-time continuous media over the Internet

El-Marakby, R.; Hutchison, David

doi:10.1109/iscc.1997.615965

Cited by 7 publications

(3 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…So, after receiving the RRs from the receivers, the sender may increase or decrease its rate of data transmission according to the packet loss fraction it received within the current interval. This rate adaptation helps to reduce network congestion and adapts to changing network conditions (Bolot, 1994), (Busse, 1996), (El-Marakby, 1997a), (El-Marakby, 1997b). The SR is useful in lip-synchronisation (inter-media synchronisation) and in calculating transmission bit rates.…”

Section: Introductionmentioning

confidence: 99%

A Scalability Scheme for the Real-time Control Protocol

El-Marakby

Hutchison

1998

High Performance Networking

Self Cite

View full text Add to dashboard Cite

Recently, some problems related to using the Real-time Control Protocol (RTCP) in very large dynamic groups have arisen. Some of these problems are: feedback delay, increasing storage state at every member, and ineffective RTCP bandwidth usage, especially for receivers that obtain incoming RTCP reports through low bandwidth links. In addition, the functionality of some fields (e.g. packet loss fraction) in the Receiver Reports (RRs) becomes questionable as, currently, an increasing number of real-time adaptive applications are using receiver-based rate adaptive schemes instead of rate adaptation schemes based on the sender. This paper presents the design of a scalable RTCP (S-RTCP) scheme. S-RTCP is based on a hierarchical structure in which members are grouped into local regions. For every region, there is an Aggregator (AG) which receives the RRs sent by its local members. The AG extracts and summarises important information in the RRs, derives some statistics, and sends them to a Manager. The Manager performs additional statistical analysis to monitor the transmission quality and to estimate regions which are suffering ma<>sively from congestion. We believe that our S-RTCP alleviates some of the RTCP scalability problems encountered in very large dynamic groups and makes effective use of RRs with regard to the current changing requirement<> of real-time adaptive applications in the Internet today.

show abstract

Section: Introductionmentioning

confidence: 99%

A Scalability Scheme for the Real-time Control Protocol

El-Marakby

Hutchison

1998

High Performance Networking

Self Cite

View full text Add to dashboard Cite

show abstract

“…(1) IF (children of CP < max num stored) NM becomes a CC; Go to (2). ELSE This CP will not send any reply back to NM; Exit, i.e.…”

Section: Local Region Establishmentmentioning

confidence: 99%

“…For example, the packet loss fraction is mainly used by sender-based adaptive applications as an indicator of congestion in the network. So, the sender increases its data transmission rate or decreases it to adapt to changing network conditions [2]. However, in receiver-based adaptive applications, there is very little significance to the packet loss parameter sent to the sender.…”

Section: Introductionmentioning

confidence: 99%

Scalability improvement of the real-time control protocol (RTCP) leading to management facilities in the Internet

El-Marakby

Hutchison²

Proceedings Third IEEE Symposium on Computers and Communications. ISCC'98. (Cat. No.98EX166)

Self Cite

View full text Add to dashboard Cite

In this paper, we address some of the problems concerning RTCP scalability in large multicast groups. The problems are summarised as the increased storage state maintained by every member about every other member in the group, the feedback delay, and the bandwidth usage problem especially for receivers that obtain incoming RTCP reports through low bandwidth links. We designed a scheme to tackle these problems and to improve the RTCP scalability. Our scheme is based on a hierarchical structure in which members are grouped dynamically into local regions and Receiver Reports (RRs) are sent with limited scope. As a result, the load is distributed among members in the group. Each region has an aggregator (AG) that receives the RRs feedback, performs some aggregation statistics on this control data, then sends these statistics to a Manager. The Manager performs additional analysis to evaluate the network performance and to estimate regions which are suffering from significant congestion. Finally, we present the benefits of using our scheme.

show abstract