Multi-User Cooperative Mobile Video Streaming: Performance Analysis and Online Mechanism Design

TL;DR

This paper introduces a cooperative framework for multi-user mobile video streaming that leverages user-provided networking, along with an online algorithm that significantly improves social welfare and bitrate performance over existing methods.

Contribution

It proposes a novel cooperative streaming framework and a Lyapunov-based online algorithm that enhances social welfare and bitrate in multi-user mobile video streaming.

Findings

Achieves 97% of the theoretical maximum social welfare.

Outperforms existing algorithms with 20-30% higher bitrate.

Provides 10-50% improvements in social welfare.

Abstract

Adaptive bitrate streaming enables video users to adapt their playing bitrates to the real-time network conditions, hence achieving the desirable quality-of-experience (QoE). In a multi-user wireless scenario, however, existing single-user based bitrate adaptation methods may fail to provide the desirable QoE, due to lack of consideration of multi-user interactions (such as the multi-user interferences and network congestion). In this work, we propose a novel user cooperation framework based on user-provided networking for multi-user mobile video streaming over wireless cellular networks. The framework enables nearby mobile video users to crowdsource their cellular links and resources for cooperative video streaming. We first analyze the social welfare performance bound of the proposed cooperative streaming system by introducing a virtual time-slotted system. Then, we design a low complexity Lyapunov-based online algorithm, which can be implemented in an online and distributed manner without the complete future and global network information. Numerical results show that the proposed online algorithm achieves an average 97% of the theoretical maximum social welfare. We further conduct experiments with real data traces, to compare our proposed online algorithm with the existing online algorithms in the literature. Experiment results show that our algorithm outperforms the existing algorithms in terms of both the achievable bitrate (with an average gain of 20% - 30%) and social welfare (with an average gain of 10% - 50%).