University of Oulu

A. Elgabli, M. Felemban and V. Aggarwal, "GroupCast: Preference-Aware Cooperative Video Streaming With Scalable Video Coding," in IEEE/ACM Transactions on Networking, vol. 27, no. 3, pp. 1138-1150, June 2019, doi: 10.1109/TNET.2019.2911523

GroupCast : preference-aware cooperative video streaming with scalable video coding

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Author: Elgabli, Anis1,2; Felemban, Muhamad1,3; Aggarwal, Vaneet4
Organizations: 1School of ECE, Purdue University, West Lafayette, IN 47907 USA
2Center of Wireless Communications, University of Oulu, 90014 Oulu, Finland
3KFUPM, Dhahran 31261, Saudi Arabia
4School of IE, Purdue University, West Lafayette, IN 47907 USA
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 2.1 MB)
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Language: English
Published: Institute of Electrical and Electronics Engineers, 2019
Publish Date: 2020-05-12


In this paper, we propose a preference-aware cooperative video streaming system for videos encoded using scalable video coding (SVC). In the proposed system, the collaborating users are interested in watching a video together on a shared screen. However, the willingness of each user to cooperate is subject to her own constraints such as user data plans. Using SVC, videos are segmented into chunks and each chunk is encoded using layers, where each layer can be fetched through any of the collaborating users. We formulate the problem of finding the optimal quality decisions and fetching policy of the SVC layers of video chunks subject to the available bandwidth, chunk deadlines, and cooperation willingness of the different users as an optimization problem. The objective is to optimize a QoE metric that maintains a trade-off between maximizing the playback rate of every chunk and ensuring fairness among all chunks to achieve the minimum skip (stall) duration without violating any of the imposed constraints. We propose an offline algorithm to solve the non-convex optimization problem when the bandwidth prediction is non-causally known. This algorithm has a run-time complexity that is polynomial in the video length and the number of collaborating users. Furthermore, we propose an online version of the algorithm for practical scenarios, where erroneous bandwidth prediction for a short window is used. Real implementation with android devices using SVC encoded video and a public dataset of bandwidth traces reveals the robustness and performance of the proposed algorithm and shows that the algorithm significantly outperforms round robin-based mechanisms in terms of avoiding skips/stalls and fetching video chunks at their highest quality possible.

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Series: IEEE/ACM transactions on networking
ISSN: 1063-6692
ISSN-E: 1558-2566
ISSN-L: 1063-6692
Volume: 27
Issue: 3
Pages: 1138 - 1150
DOI: 10.1109/TNET.2019.2911523
Type of Publication: A1 Journal article – refereed
Field of Science: 213 Electronic, automation and communications engineering, electronics
Funding: This work was supported in part by the U.S. National Science Foundation under Grant CCF-1527486 and Grant CNS-1618335.
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