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

Kurdoglu, Eymen; Liu, Yong; Wang, Yao; Shi, Yu; Gu, Chenchen; Lyu, Jing

doi:10.1145/2910017.2910608

Cited by 43 publications

(23 citation statements)

References 17 publications

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“…As an example, the inter-download times of video segments are predicted in [102], where the output sequences are the interdownload times of the already downloaded segments and the states are the instants of the next download request. ARIMA: [13], [38], [40], [46], [47], [54], [58], [59], [63], [100], [119] Kalman: [32], [ CF: [16], [134], [149] Cluster: [15], [34], [51], [117], [122], [123], [148], [156] Decision trees: [35], [98], [ Functional: [28], [29], [38], [64], [99], [104], [105] SVM: [51], [114], [139] ANN: [14], [48], [106], [ 2) Bayesian inference: This approach allows to make statements about what is unknown, by conditioning on what is known. Bayesian prediction can be summarized in the following steps: 1) define a model that expresses qualitative aspects of our knowledge but has unknown parameters, 2) specify a prior probability distribution for the unknown parameters, 3) compute the posterior probability distribution for the parameters, given the observed data, and 4) make predictions by averaging ove...…”

Section: Statistical Methods For Probabilistic Forecastingmentioning

confidence: 99%

See 1 more Smart Citation

A Survey of Anticipatory Mobile Networking: Context-Based Classification, Prediction Methodologies, and Optimization Techniques

Bui

Cesana

Hosseini³

et al. 2017

IEEE Commun. Surv. Tutorials

216

137

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A growing trend for information technology is to not just react to changes, but anticipate them as much as possible. This paradigm made modern solutions, such as recommendation systems, a ubiquitous presence in today's digital transactions. Anticipatory networking extends the idea to communication technologies by studying patterns and periodicity in human behavior and network dynamics to optimize network performance. This survey collects and analyzes recent papers leveraging context information to forecast the evolution of network conditions and, in turn, to improve network performance. In particular, we identify the main prediction and optimization tools adopted in this body of work and link them with objectives and constraints of the typical applications and scenarios. Finally, we consider open challenges and research directions to make anticipatory networking part of next generation networks.

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Section: Statistical Methods For Probabilistic Forecastingmentioning

confidence: 99%

“…Video calls are considered in [63]. Namely, a cross-layer design for proactive congestion control, named Rebera, is proposed.…”

Section: B Link Contextmentioning

confidence: 99%

A Survey of Anticipatory Mobile Networking: Context-Based Classification, Prediction Methodologies, and Optimization Techniques

Bui

Cesana

Hosseini³

et al. 2017

IEEE Commun. Surv. Tutorials

216

137

View full text Add to dashboard Cite

show abstract

“…In the beginning of each new segment, we predict the average sustainable throughput from the sender to the receiver based on the measured throughput in the past segments fedback by the receiver. In a prior work [10] on rate adaptation for video calls, an online linear adaptive filter called recursive least square (RLS) was found to achieve higher prediction accuracy than exponentially weighted moving average. Therefore, we adopt the RLS method in this work and use the measured bandwidth in previous two segments for the prediction.…”

Section: Segment-level Bandwidth Predictionmentioning

confidence: 99%

Low-latency FoV-adaptive Coding and Streaming for Interactive 360° Video Streaming

Mao

Sun

Liu

et al. 2020

Proceedings of the 28th ACM International Conference on Multimedia

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In 360 • video interactive streaming, it is critical to minimize the end-to-end frame delay. It is also important to predict the user's field of video (FoV) and allocate more bits in regions within the predicted FoV. Towards both goals, we propose a low-delay FoVadaptive coding and delivery system that is robust to bandwidth variations and FoV prediction errors. Each frame is coded only in the predicted FoV (PF), a border surrounding the predicted FoV (PF+), and a rotating intra (RI) region. To maximize the coding efficiency, the PF and PF+ regions are coded with temporal and spatial prediction, while the RI region is coded with spatial prediction only. The RI region enables periodic refreshment of the entire frame and provides robustness to both FoV prediction errors and frame losses. The total bit budget is adapted both at the segment level based on the predicted average bandwidth for the segment and at the frame level based on the sender buffer status, to ensure timely delivery. The system further adapts the sizes and coding rates of different regions for each video segment to maximize the average rendered video quality under the total bit budget. To enable such adaptation, we propose novel ways to model the quality-rate (Q-R) relations of coded regions that take into account of potentially misaligned coded regions in successive frames due to FoV dynamics. We examine the performance of the proposed system and three benchmark systems, under real-world bandwidth traces and FoV traces, and demonstrate that the proposed system can significantly improve the rendered video quality over the benchmark systems. Furthermore, the proposed system can achieve very low end-to-end frame delay while maintaining a low frame freeze probability and providing smooth video playback. CCS CONCEPTS • Human-centered computing → Virtual reality; • Information systems → Multimedia streaming.

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“…GCC takes one way delay gradient for congestion signal, NADA takes an aggregated delay signal and SCReAM takes one way delay for rate control. Rebera [26] proactively measures the available bandwidth by packet trains, and determines a rate budget predicted from history information for the video encoder. It aims to provide easy rate adaption, low eoncoding complexity and low delay.…”

Section: Related Workmentioning

confidence: 99%

Congestion Control for RTP Media: A Comparison on Simulated Environment

Zhang

Lei

Zhang

et al. 2019

Simulation Tools and Techniques

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To develop low latency congestion control algorithm for real time ta c has been gained a ention recently. RTP Media Congestion Avoidance Techniques (RMCAT) working group was initiated for standard de nation. ere are three algorithms under this group, Network Assisted Dynamic Adaptation (NADA) proposed by Cisco, Google Congestion Control (GCC) proposed by Google and Self-Clocked Rate Adaptation for Multimedia(SCReAM) proposed by Ericsson. is paper compares and analyses the performance of these algorithms on simulation environment. Results show GCC has well fairness property and performs well in lossy link but slow convergence in dynamic link, NADA stabilizes its rate quickly but su ers "late-comer" e ect, SCReAM has the lowest queue occupation but also lower link capacity utilization.

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

Cited by 43 publications

References 17 publications

A Survey of Anticipatory Mobile Networking: Context-Based Classification, Prediction Methodologies, and Optimization Techniques

A Survey of Anticipatory Mobile Networking: Context-Based Classification, Prediction Methodologies, and Optimization Techniques

Low-latency FoV-adaptive Coding and Streaming for Interactive 360° Video Streaming

Congestion Control for RTP Media: A Comparison on Simulated Environment

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