Joint Optimization of QoE and Fairness Through Network Assisted Adaptive Mobile Video Streaming

TL;DR

This paper proposes a network-assisted adaptive streaming framework that jointly optimizes user experience and fairness, outperforming traditional client-based DASH through coordinated bitrate selection and resource management.

Contribution

It introduces a multi-servers multi-coordinators framework and formulates an optimization problem for joint QoE and fairness enhancement in mobile video streaming.

Findings

Improved QoE and fairness compared to client-based DASH.

Effective heuristic solution for resource allocation.

Simulation results validate the proposed approach.

Abstract

MPEG has recently proposed Server and Network Assisted Dynamic Adaptive Streaming over HTTP (SAND-DASH) for video streaming over the Internet. In contrast to the purely client-based video streaming in which each client makes its own decision to adjust its bitrate, SAND-DASH enables a group of simultaneous clients to select their bitrates in a coordinated fashion in order to improve resource utilization and quality of experience. In this paper, we study the performance of such an adaptation strategy compared to the traditional approach with large number of clients having mobile Internet access. We propose a multi-servers multi-coordinators (MSs-MCs) framework to model groups of remote clients accessing video content replicated to spatially distributed edge servers. We then formulate an optimization problem to maximize jointly the QoE of individual clients, proportional fairness in allocating the limited resources of base stations as well as balancing the utilized resources among multiple serves. We then present an efficient heuristic-based solution to the problem and perform simulations in order to explore parameter space of the scheme as well as to compare the performance to purely client-based DASH.