A Control-Theoretic Approach to Adaptive Video Streaming in Dense Wireless Networks

Abstract

Recently, the way people consume video content has been undergoing a dramatic change. Plain TV sets, that have been the center of home entertainment for a long time, are losing ground to hybrid TVs, PCs, game consoles, and, more recently, mobile devices such as tablets and smartphones. The new predominant paradigm is: watch what I want, when I want, and where I want. The challenges of this shift are manifold. On the one hand, broadcast technologies such as DVB-T/C/S need to be extended or replaced by mechanisms supporting asynchronous viewing, such as IPTV and video streaming over best-effort networks, while remaining scalable to millions of users. On the other hand, the dramatic increase of wireless data traffic begins to stretch the capabilities of the existing wireless infrastructure to its limits. Finally, there is a challenge to video streaming technologies to cope with a high heterogeneity of end-user devices and dynamically changing network conditions, in particular in wireless and mobile networks. In the present work, our goal is to design an efficient system that supports a high number of unicast streaming sessions in a dense wireless access network. We address this goal by jointly considering the two problems of wireless transmission scheduling and video quality adaptation, using techniques inspired by the robustness and simplicity of proportional-integral-derivative (PID) controllers. We show that the control-theoretic approach allows to efficiently utilize available wireless resources, providing high quality of experience (QoE) to a large number of users.Index Terms-HTTP-based adaptive streaming, MPEG-DASH, small-cell wireless networks, streaming media.

Understanding Video Streaming Algorithms in the Wild

“…In stable state, Fandom switches substantially more than SRF. We also evaluated the academic (Robust) MPC algorithm [15] on the same network traces and over the SRF videos. The MPC algorithm would use more than twice as much switching both in startup and later, compared to SRF's deployed ABR.…”

“…QoE goal: Academic ABR work has largely used a QoE metric that linearly combines a reward for high bitrate with penalties for rebuffers and quality switches [15,14]. More recent work has suggested formulations of QoE that reward perceptual video quality rather than just bitrate [18].…”

“…We then simulate playback using the same network traces up until the same point offline for academic ABRs as we do for the deployed ones. We primarily rely on Robust MPC [15] (referred to throughout as MPC) as a stand-in for a recent, high-quality academic ABR approach. While even newer proposals are available, they either use data-dependent learning techniques [14,4] that are unnecessary for our purpose of gaining intuition, or do not have available, easy-to-use code.…”

Dynamic Resource Allocation and Layer Selection for Scalable Video Streaming in Femtocell Networks: A Twin-Time-Scale Approach

“…However, they mainly focus their attention on scheduling the access to both the Macrocell Base Station(MBS) and to the FBS. In [29] and [30], the authors jointly consider the wireless transmission scheduling and video quality adaptation in dense wireless networks. In [31], time-domain resource partitioning between the macrocell and small cells is invoked for optimizing the delivery of Dynamic Adaptive Streaming over HTTP (DASH).…”

“…Xu et al [32] present a video qualityaware mobile association, whilst giving cognizance both to the spectral and energy efficiency of two-tier heterogeneous networks. However, although the above-mentioned literature [17], [29], [30], [32] discusses adaptive video transmissions in heterogeneous wireless networks, none of them considers the cost levied due to the inference imposed by the small cells on the macrocell. Furthermore, the time scales of the video adaptation and the wireless resource allocation are very different in practical systems, which should be prudently considered, when streaming video over heterogeneous wireless networks.…”