University of Oulu

A. Elgabli and V. Aggarwal, "SmartStreamer: Preference-Aware Multipath Video Streaming Over MPTCP," in IEEE Transactions on Vehicular Technology, vol. 68, no. 7, pp. 6975-6984, July 2019, doi: 10.1109/TVT.2019.2915355

SmartStreamer : preference-aware multipath video streaming over MPTCP

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Author: Elgabli, Anis1,2; Aggarwal, Vaneet3
Organizations: 1School of Electrical Computer Engineering, Purdue University, West Lafayette, IN 47907 USA
2Center of Wireless Communications, University of Oulu, Oulu 90014, Finland
3School of Industrial Engineering and the School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN 47907 USA
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 0.6 MB)
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Language: English
Published: Institute of Electrical and Electronics Engineers, 2020
Publish Date: 2020-11-13


Simultaneous access to multiple interfaces (e.g., WiFi and cellular networks) can significantly improve the users’ quality of experience (QoE) in video streaming. However, some interfaces could be more expensive to use and less energy efficient. Therefore, in this paper, we propose a preference-aware multipath video streaming algorithm over HTTP using multipath TCP (MPTCP). First, we formulate the quality decisions of the video chunks and the chunk’s download policy subject to the chunk’s deadlines, the available bandwidth of the different paths, and the link preferences as a non-convex optimization problem. The objective is to optimize a novel QoE metric that maintains a tradeoff between maximizing the quality of every video’s chunk and ensuring quality fairness among all chunks for the minimum re-buffering (stall) duration, and without violating the link preference constraint. Second, we develop a polynomial time complexity algorithm to solve the proposed optimization problem, and provide guarantees for the proposed algorithm. We further propose a sliding window based online algorithm where several challenges including short bandwidth prediction with prediction errors are addressed. Extensive emulated experiments with real bandwidth traces of public datasets reveal the robustness of our scheme and demonstrate its significant performance improvement compared to the state-of-the-art multi-path streaming algorithms.

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Series: IEEE transactions on vehicular technology
ISSN: 0018-9545
ISSN-E: 1939-9359
ISSN-L: 0018-9545
Volume: 68
Issue: 7
Pages: 6975 - 6984
DOI: 10.1109/TVT.2019.2915355
Type of Publication: A1 Journal article – refereed
Field of Science: 213 Electronic, automation and communications engineering, electronics
Funding: This work was supported by the U.S. National Science Foundation under Grants CCF-1527486 and CNS-1618335.
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