Adaptive Multicast of Multi-Layered Video: Rate-Based and Credit-Based Approaches

TL;DR

This paper compares rate-based and credit-based adaptive multicast mechanisms for multi-layered video, evaluating their performance in terms of responsiveness, bandwidth utilization, scalability, and fairness through simulations.

Contribution

It introduces and evaluates two adaptive multicast mechanisms for multi-layered video, highlighting their performance trade-offs and suitability under varying network conditions.

Findings

Both mechanisms provide high-quality video despite bandwidth variability.

Rate-based approach offers quicker responsiveness to network changes.

Credit-based approach demonstrates better fairness and scalability.

Abstract

Network architectures that can efficiently transport high quality, multicast video are rapidly becoming a basic requirement of emerging multimedia applications. The main problem complicating multicast video transport is variation in network bandwidth constraints. An attractive solution to this problem is to use an adaptive, multi-layered video encoding mechanism. In this paper, we consider two such mechanisms for the support of video multicast; one is a rate-based mechanism that relies on explicit rate congestion feedback from the network, and the other is a credit-based mechanism that relies on hop-by-hop congestion feedback. The responsiveness, bandwidth utilization, scalability and fairness of the two mechanisms are evaluated through simulations. Results suggest that while the two mechanisms exhibit performance trade-offs, both are capable of providing a high quality video service in the presence of varying bandwidth constraints.