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11
Confused, Timid, and Unstable: Picking a Video Streaming Rate is Hard
- In ACM Internet Measurement Conference
, 2012
"... Today’s commercial video streaming services use dynamic rateselectiontoprovideahigh-qualityuserexperience. Most services host content on standard HTTP servers in CDNs, so rate selection must occur at the client. We measure three popular video streaming services – Hulu, Netflix, and Vudu – and find t ..."
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Today’s commercial video streaming services use dynamic rateselectiontoprovideahigh-qualityuserexperience. Most services host content on standard HTTP servers in CDNs, so rate selection must occur at the client. We measure three popular video streaming services – Hulu, Netflix, and Vudu – and find that accurate client-side bandwidth estimation above the HTTP layer is hard. As a result, rate selection based on inaccurate estimates can trigger a feedback loop, leading to undesirably variable and low-quality video. We call this phenomenon the downward spiral effect, and we measure it on all three services, present insights into its root causes, and validate initial solutions to prevent it.
HTTP-based Adaptive Streaming for Mobile Clients using Markov Decision Process
- In Packet Video Workshop (PV
, 2013
"... Abstract—Due to its simplicity at the server side, HTTP-based adaptive streaming has become a popular choice for streaming on-line contents to a wide range of user devices. In HTTP-based streaming systems, the server simply stores the video segmented into a series of small chunks coded in many diffe ..."
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Abstract—Due to its simplicity at the server side, HTTP-based adaptive streaming has become a popular choice for streaming on-line contents to a wide range of user devices. In HTTP-based streaming systems, the server simply stores the video segmented into a series of small chunks coded in many different qualities and sizes, and leaves the decision of which chunk to download next to achieve a high quality viewing experience to the client. This decision making is a challenging task, especially in mobile environment due to unexpected changes in network bandwidth as the user moves through different regions. In this paper, we consider Markov Decision Process (MDP) to derive the optimum chunk selection strategy that maximizes streaming quality and propose three approaches to reduce the computational cost of MDP. The first approach recomputes the solution after downloading every k chunks. The second approach computes the solution once using global network statistics of a given region. The third approach recomputes the solution every x meters using offline statistics for each x meters of the road. The three approaches are compared using real-world 3G bandwidth and mobility traces. The best performance is achieved with x-MDP. I.
Using the buffer to avoid rebuffers: Evidence from a large video streaming service
- ArXiv
"... To provide a better streaming experience, video clients today select their video rates by observing and esti-mating the available capacity. Recent work has shown that capacity estimation is fraught with difficulties be-cause of complex interactions between the ABR con-trol loop, HTTP server performa ..."
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To provide a better streaming experience, video clients today select their video rates by observing and esti-mating the available capacity. Recent work has shown that capacity estimation is fraught with difficulties be-cause of complex interactions between the ABR con-trol loop, HTTP server performance and TCP conges-tion control. Estimation-based rate selection algorithms can lead to unnecessary rebuffering events and subopti-mal video quality. This paper argues that we should do away with estimating network capacity, and instead di-rectly observe and control the playback buffer—which is the state variable we are most interested in control-ling. We present a class of “buffer-based ” rate selection algorithms that reduce the rebuffering rate while allow-ing us to control the delivered video quality. We imple-mented our algorithms inside the Netflix video client and ran a series of experiments spanning millions of Netflix users around the world. Our results show that by doing away with estimating network capacity and instead fo-cusing on buffer occupancy, we can reduce rebuffer rates by 20 % while holding video rate constant. 1
A Real-Time Adaptive Algorithm for Video Streaming over Multiple Wireless Access Networks
"... Abstract—Video streaming is gaining popularity among mobile users. The latest mobile devices, such as smart phones and tablets, are equipped with multiple wireless network interfaces. How to efficiently and cost-effectively utilize multiple links to improve video streaming quality needs investigatio ..."
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Abstract—Video streaming is gaining popularity among mobile users. The latest mobile devices, such as smart phones and tablets, are equipped with multiple wireless network interfaces. How to efficiently and cost-effectively utilize multiple links to improve video streaming quality needs investigation. In order to maintain high video streaming quality while reducing the wireless service cost, in this paper, the optimal video streaming process with multiple links is formulated as a Markov Decision Process (MDP). The reward function is designed to consider the quality of service (QoS) requirements for video traffic, such as the startup latency, playback fluency, average playback quality, playback smoothness and wireless service cost. To solve the MDP in real time, we propose an adaptive, best-action search algorithm to obtain a sub-optimal solution. To evaluate the performance of the proposed adaptation algorithm, we implemented a testbed using the Android mobile phone and the Scalable Video Coding (SVC) codec. Experiment results demonstrate the feasibility and effectiveness of the proposed adaptation algorithm for mobile video streaming applications, which outperforms the existing state-of-the-art adaptation algorithms. Index Terms—DASH, Markov decision process, video stream-ing, multiple links. I.
Transmission control for compressive sensing video over wireless channel
- IEEE Trans. Wireless Commun
, 2013
"... Abstract—In this paper, we consider a wireless sensor node monitoring the environment and it is equipped with a compressive-sensing based, single-pixel image camera and other sensors such as temperature and humidity sensors. The wireless node needs to send the data out in a timely and energy efficie ..."
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Abstract—In this paper, we consider a wireless sensor node monitoring the environment and it is equipped with a compressive-sensing based, single-pixel image camera and other sensors such as temperature and humidity sensors. The wireless node needs to send the data out in a timely and energy efficient way. This transmission control problem is challenging in that we need to jointly consider perceived video quality, quality variation, power consumption and transmission delay requirements, and the wireless channel uncertainty. We address the above issues by first building a rate-distortion model for compressive sensing video. Then we formulate the deterministic and stochastic optimization problems and design the transmission control algorithm which jointly performs rate control, scheduling and power control. Extensive simulations have been conducted to demonstrate the effectiveness of the proposed transmission control algorithm. Index Terms—Compressive sensing video, stochastic optimiza-tion, rate-distortion, video transmission. I.
Energy and Computing Ressource Aware Feedback Control Strategies for H.264 Video Decoding
"... Abstract: Embedded devices using highly integrated chips must cope with conflicting constraints, while executing computationally demanding applications under limited energy storage. Automatic control and feedback loops appear to be an effective solution to simultaneously accommodate for performance ..."
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Abstract: Embedded devices using highly integrated chips must cope with conflicting constraints, while executing computationally demanding applications under limited energy storage. Automatic control and feedback loops appear to be an effective solution to simultaneously accommodate for performance uncertainties due to the tiny scale gates variability, varying and poorly predictable computing demands and limited energy storage constraints. This report presents the practical example of an embedded video decoder controlled by several cascaded feedback loops to carry out the trade-off between decoding quality and energy consumption, exploiting the frequency and voltage scaling capabilities of the chip. The inner loop controls the Dynamic Voltage and Frequency Scaling (DVFS) through a fast predictive control strategy to adapt the computing speed of the chip to the demands of the video flow decoder. The outer loop is fed back with measures coming from the current frame decoding execution, and computes the scheduling set-points needed by the inner loop to process the next frame decoding. The feedback loops have been implemented on a standard PC and some experimental results are provided. It is shown that a noticeable reduction of the energy consumption can be achieved through a very small execution overhead while preserving a requested decoding quality, and that the robustness of feedback
Scalable Video Transmission over Wireless Networks
, 2013
"... permission of the author. ii ..."
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Dynamic Adaptive Streaming over Popularity-driven Caching in Information-Centric Networks
"... Abstract-The growing demand for video streaming is straining the current Internet, and mandating a novel approach to future Internet paradigms. The advent of Information-Centric Networks (ICN) promises a novel architecture for addressing this exponential growth in data-intensive services, of which ..."
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Abstract-The growing demand for video streaming is straining the current Internet, and mandating a novel approach to future Internet paradigms. The advent of Information-Centric Networks (ICN) promises a novel architecture for addressing this exponential growth in data-intensive services, of which video streaming is projected to dominate (in traffic size). In this paper, we present a novel strategy in ICNs for adaptive caching of variable video contents tailored to different sizes and bit rates. Our objective is to achieve optimal video caching to reduce access time for the maximal requested bit rate for every user. At its core, our approach capitalizes on a rigorous delay analysis and potentiates maximal serviceability for each user. We incorporate predictors for requested video objects based on a popularity index (Zipf distribution). In our proposed model, named DASCache, we present delay queuing analysis for cached objects, providing a cap on expected delay in accessing video content. In DASCache, we present a Binary Integer Programming (BIP) formulation for the cache assignment problem, which operates in rounds based on changes in content requests and popularity scores. DASCache reacts to changes in network dynamics that impact bit rate choices by heterogeneous users and enables users to stream videos, maximizing Quality of Experience (QoE). To evaluate the performance of DASCache, in contrast to current benchmarks in video caching, we present an elaborate performance evaluation carried out on ndnSIM, over NS-3.
Adaptive Video Streaming over Whitespace: SVC for 3-Tiered Spectrum Sharing
"... Abstract—The recently proposed 3-Tier access model for ..."
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AdapComm: A Bandwidth Allocation Methodology for Multimedia Applications in Wireless Networks
"... In this article, we propose AdaptMetric Communication (Adap-Comm), an end-to-end bandwidth estimation and allocation methodology putting emphasis on Quality of Experience at the user side. AdapComm dynamically samples the con-nection by sending dummy probing-TCP packets and de-rives the bandwidth on ..."
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In this article, we propose AdaptMetric Communication (Adap-Comm), an end-to-end bandwidth estimation and allocation methodology putting emphasis on Quality of Experience at the user side. AdapComm dynamically samples the con-nection by sending dummy probing-TCP packets and de-rives the bandwidth online. This information is then sent to the server to adaptively change the data transmission to maintain user experience even in highly fluctuating net-works, such as wireless connections. In future office-works, the usage of multimedia in mobile environments will be the norm, thus, we demonstrate the implementation of smooth, stall-free video streaming based on this scheme for enhanced user experience. Categories and Subject Descriptors H.5 [Information Interfaces and Presentation]: Mul-timedia Information System—Evaluation/methodology; C.2