LBP: Robust Rate Adaptation Algorithm for SVC Video Streaming
Anis Elgabli, Vaneet Aggarwal, Shuai Hao, Feng Qian and, Subhabrata Sen

TL;DR
This paper introduces LBP, a robust rate adaptation algorithm for SVC video streaming over variable networks, optimizing quality, minimizing stalls, and reducing quality switches with linear complexity.
Contribution
We formulate an optimization problem for SVC streaming quality decisions and develop LBP, an optimal, low-complexity algorithm, along with an online version for real-time adaptation.
Findings
LBP achieves optimal solutions with linear complexity.
Extensive simulations show significant performance improvements.
Real LTE traces validate practical deployability.
Abstract
Video streaming today accounts for up to 55\% of mobile traffic. In this paper, we explore streaming videos encoded using Scalable Video Coding scheme (SVC) over highly variable bandwidth conditions such as cellular networks. SVC's unique encoding scheme allows the quality of a video chunk to change incrementally, making it more flexible and adaptive to challenging network conditions compared to other encoding schemes. Our contribution is threefold. First, we formulate the quality decisions of video chunks constrained by the available bandwidth, the playback buffer, and the chunk deadlines as an optimization problem. The objective is to optimize a novel QoE metric that models a combination of the three objectives of minimizing the stall/skip duration of the video, maximizing the playback quality of every chunk, and minimizing the number of quality switches. Second, we develop Layered…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
