Multicast scheduling for scalable video streaming in wireless networks

Abstract

We consider how relatively simple extensions of popular channelaware schedulers can be used to multicast scalable video streams in high speed radio access networks. To support the evaluation, we first describe a model of the channel distortion of scalable video coding and validate it using eight commonly used test sequences. We use the distortion model in a detailed simulation setup to compare the performance of six schedulers, among them the Max-Sum and Max-Prod schedulers, which aim to maximize the sum and the product of streaming utilities, respectively. We investigate how the traffic load, user mobility, layering structure, and users' aversion of fluctuating distortion influence the streaming performance. Our results show that the Max-Sum scheduler performs better than other considered schemes in almost all scenarios. With the Max-Sum scheduler, the gain of scalable video coding compared to non-scalable coding is substantial, even when users do not tolerate frequent changes in video quality.

QoE optimization of video multicast with heterogeneous channels and playback requirements

“…Sharangi et al [17] proposed a scalable video transmission scheduling optimization scheme for multiple multicasts to share a set of WiMax timeslots such that the average utility of the multicasts is maximized. A similar work with a more elaborate model of physical layer parameters and channel effects is proposed by Vukadinovic et al [18]. While our problem (described below) and [17,18] both strive to balance serving individual clients versus overall throughput, for our problem the individuals are clients with heterogeneous channels and playback requirements within a multicast, whereas for [17,18] the individuals are distinct multicasts each of which targeting one channel and one media quality.…”

“…Subsequently, unequal error protection (UEP) was proposed [5] and its application to multimedia transmission was studied [6]. Further works largely fall into one of the following three categories: AL-FEC design for UEP [7][8][9][10][11][12][13], link layer scheduling [14][15][16][17][18], and joint source-channel coding [19]. In practice, system design and provisioning usually prefer separate source and channel coding as well as low computation complexity.…”

Transmitting Scalable Video Streaming over Wireless Ad Hoc Networks

“…Vladimir and Dan [25] defined a model for the channel distortion of scalable video coding. The proposed model considers the parameters that strongly influence the performance of streaming media, either directly or indirectly, such as traffic load, mobility, and users' dislike of fluctuating distortion.…”

A Channel-Aware and Occupancy-Dependent Scheduler for Video Transmission over Wireless Channels

“…The authors considered the problem of choosing the best streaming policy for optimal distortion multi-path video delivery using a fast heuristic-based streaming scenarios. In [25] the idea of channel-aware schedulers is extended to multicast Max-Sum scheduler that is combined with scalable video streaming. The authors in [25] aimed at the maximization of the sum and the product of streaming utilities.…”

“…In [25] the idea of channel-aware schedulers is extended to multicast Max-Sum scheduler that is combined with scalable video streaming. The authors in [25] aimed at the maximization of the sum and the product of streaming utilities.…”