Performance Bound Analysis for Crowdsourced Mobile Video Streaming

TL;DR

This paper introduces a crowdsourced mobile video streaming framework that enables cooperative resource sharing among users and analyzes its social welfare performance bounds using a virtual synchronized system model.

Contribution

It proposes a novel crowdsourced streaming framework and derives theoretical performance bounds to benchmark future algorithms and incentive mechanisms.

Findings

Performance bounds serve as benchmarks for system optimization.

Virtual synchronized system effectively bounds asynchronous system performance.

Framework enables cooperative resource sharing among mobile video users.

Abstract

Adaptive bitrate (ABR) streaming enables video users to adapt the playing bitrate to the real-time network conditions to achieve the desirable quality of experience (QoE). In this work, we propose a novel crowdsourced streaming framework for multi-user ABR video streaming over wireless networks. This framework enables the nearby mobile video users to crowdsource their radio links and resources for cooperative video streaming. We focus on analyzing the social welfare performance bound of the proposed crowdsourced streaming system. Directly solving this bound is challenging due to the asynchronous operations of users. To this end, we introduce a virtual time-slotted system with the synchronized operations, and formulate the associated social welfare optimization problem as a linear programming. We show that the optimal social welfare performance of the virtual system provides effective upper-bound and lower-bound for the optimal performance (bound) of the original asynchronous system, hence characterizes the feasible performance region of the proposed crowdsourced streaming system. The performance bounds derived in this work can serve as a benchmark for the future online algorithm design and incentive mechanism design.