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Title: VOXEL: cross-layer optimization for video streaming with imperfect transmission
Delivering videos under less-than-ideal network conditions without compromising end-users' quality of experiences is a hard problem. Virtually all prior work follow a piecemeal approach---either "tweaking" the fully reliable transport layer or making the client "smarter." We propose VOXEL, a cross-layer optimization system for video streaming. We use VOXEL to demonstrate how to combine application-provided "insights" with a partially reliable protocol for optimizing video streaming. To this end, we present a novel ABR algorithm that explicitly trades off losses for improving end-users' video-watching experiences. VOXEL is fully compatible with DASH, and backward-compatible with VOXEL-unaware servers and clients. In our experiments emulating a wide range of network conditions, VOXEL outperforms the state-of-the-art: We stream videos in the 90th-percentile with up to 97% less rebuffering than the state-of-the-art without sacrificing visual fidelity. We also demonstrate the benefits of VOXEL for small-buffer regimes like the emerging use case of low-latency and live streaming. In a survey of 54 real users, 84% of the participants indicated that they prefer videos streamed using VOXEL compared to the state-of-the-art.  more » « less
Award ID(s):
1763617 1901137
PAR ID:
10346185
Author(s) / Creator(s):
; ; ; ; ;
Date Published:
Journal Name:
International Conference on emerging Networking EXperiments and Technologies (CoNEXT'21)
Page Range / eLocation ID:
359 to 374
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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