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Real-time bandwidth prediction and rate adaptation for video calls over cellular networks

Published: 10 May 2016 Publication History

Abstract

We study interactive video calls between two users, where at least one of the users is connected over a cellular network. It is known that cellular links present highly-varying network bandwidth and packet delays. If the sending rate of the video call exceeds the available bandwidth, the video frames may be excessively delayed, destroying the interactivity of the video call. In this paper, we present Rebera, a cross-layer design of proactive congestion control, video encoding and rate adaptation, to maximize the video transmission rate while keeping the one-way frame delays sufficiently low. Rebera actively measures the available bandwidth in real-time by employing the video frames as packet trains. Using an online linear adaptive filter, Rebera makes a history-based prediction of the future capacity, and determines a bit budget for the video rate adaptation. Rebera uses the hierarchical-P video encoding structure to provide error resilience and to ease rate adaptation, while maintaining low encoding complexity and delay. Furthermore, Rebera decides in real time whether to send or discard an encoded frame, according to the budget, thereby preventing self-congestion and minimizing the packet delays. Our experiments with real cellular link traces demonstrate Rebera can, on average, deliver higher bandwidth utilization and shorter packet delays than Apple's FaceTime.

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          cover image ACM Conferences
          MMSys '16: Proceedings of the 7th International Conference on Multimedia Systems
          May 2016
          420 pages
          ISBN:9781450342971
          DOI:10.1145/2910017
          • General Chair:
          • Christian Timmerer
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          Published: 10 May 2016

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          Author Tags

          1. cross-layer
          2. forecasting
          3. hierarchical-p
          4. real-time

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          • Research-article

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          • Tencent Inc.

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          MMSys'16
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          MMSys'16: Multimedia Systems Conference 2016
          May 10 - 13, 2016
          Klagenfurt, Austria

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          MMSys '16 Paper Acceptance Rate 20 of 71 submissions, 28%;
          Overall Acceptance Rate 176 of 530 submissions, 33%

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          • (2024)5G Edge Vision: Wearable Assistive Technology for People with Blindness and Low Vision2024 IEEE Wireless Communications and Networking Conference (WCNC)10.1109/WCNC57260.2024.10570607(1-6)Online publication date: 21-Apr-2024
          • (2024)UplinkNet: Practical Commercial 5G Standalone (SA) Uplink Throughput Prediction2024 IEEE International Conference on Visual Communications and Image Processing (VCIP)10.1109/VCIP63160.2024.10849914(1-5)Online publication date: 8-Dec-2024
          • (2024)BandSeer: Bandwidth Prediction for Cellular Networks2024 IEEE 49th Conference on Local Computer Networks (LCN)10.1109/LCN60385.2024.10639706(1-8)Online publication date: 8-Oct-2024
          • (2024)Learning-Based Transport Control Adapted to Non-Stationarity for Real-Time Communication2024 IEEE/ACM 32nd International Symposium on Quality of Service (IWQoS)10.1109/IWQoS61813.2024.10682855(1-10)Online publication date: 19-Jun-2024
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          • (2024)BitFormer: Transformer-Based Neural Network for Bitrate Prediction in Real-Time Communications2024 IEEE 21st Consumer Communications & Networking Conference (CCNC)10.1109/CCNC51664.2024.10454679(65-70)Online publication date: 6-Jan-2024
          • (2024)DeX: Deep learning-based throughput prediction for real-time communications with emphasis on traffic eXtremesComputer Networks10.1016/j.comnet.2024.110507249(110507)Online publication date: Jul-2024
          • (2023)Octopus: In-Network Content Adaptation to Control Congestion on 5G LinksProceedings of the Eighth ACM/IEEE Symposium on Edge Computing10.1145/3583740.3628438(199-214)Online publication date: 6-Dec-2023
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