Video Streaming System Research Articles

Query Adaptation Techniques in Temporal-DHT for P2P Media Streaming Applications

Peer-to-Peer (P2P)-based approach for on-demand video streaming systems (P2P-VoD) characterized by asynchronous user-interactivity has proven to be practical and effective in recent years with real-world Internet-scale deployment (Huang, Li, & Ross, 2007). Current state-of-art P2P-VoD systems employ tracker server for discovering content suppliers which poses scalability and bottleneck issues. Temporal-DHT is a structured P2P based approach which can efficiently accommodate the large number of update operations with the continuous change of user’s playing position and supporting asynchronous jumps (Bhattacharya, Yang, & Zhang, 2010). The authors propose different query adaptation strategies based upon content popularity distributions and shortage bandwidth ratios which are proved to be effective in improving the performance of P2P streaming system by deriving certain optimized solutions. They formulate valuable optimization problems in the context of a P2P-VoD system such as minimization of query search cost, server bandwidth consumption, and a joint cost-load framework. The authors provide optimized solutions that achieve the best result for the above mentioned optimization objectives. They show extensive simulation studies under various scenarios of search cost, streaming quality, and other associated factors in a dynamic network environment where users are free to asynchronously join/leave the system.

Video streaming using a location-based bandwidth-lookup service for bitrate planning

A lot of people around the world commute using public transportation and would like to spend this time viewing streamed video content such as news or sports updates. However, mobile wireless networks typically suffer from severe bandwidth fluctuations, and the networks are often completely unresponsive for several seconds, sometimes minutes. Today, there are several ways of adapting the video bitrate and thus the video quality to such fluctuations, for example, using scalable video codecs or segmented adaptive HTTP streaming that switches between nonscalable video streams encoded in different bitrates. Still, for a better long-term video playout experience that avoids disruptions and frequent quality changes while using existing video adaptation technology, it is desirable to perform bandwidth prediction and planned quality adaptation. This article describes a video streaming system for receivers equipped with a GPS. A receiver's download rate is constantly monitored, and periodically reported back to a central database along with associated GPS positional data. Thus, based on the current location, a streaming device can use a GPS-based bandwidth-lookup service in order to better predict the near-future bandwidth availability and create a schedule for the video playout that takes likely future availability into account. To create a prototype and perform initial tests, we conducted several field trials while commuting using public transportation. We show how our database has been used to predict bandwidth fluctuations and network outages, and how this information helps maintain uninterrupted playback with less compromise on video quality than possible without prediction.

클라우드 컴퓨팅 환경에서의 네트워크 적응적 N-스크린 게임 시스템

본 논문은 클라우드 컴퓨팅 환경에서 새로운 네트워크 적응적 N-스크린 게임 시스템을 설계 및 구현하였다. 목표하는 시스템은 클라우드 서버에서 연산된 게임 화면을 가정에 설치된 게임서버를 통해 한대 이상의 게임 단말로 전송해야 한다. 하지만, 하나의 게임 영상을 가지고 서로 다른 해상도를 가진 N-스크린을 지원하는 것은 어렵고, 무선 네트워크에서의 게임 사용자 이동은 영상 화질을 저하시킨다. 따라서, 본 논문은 스케일러블 비디오 코딩 기술과 채널 코드 기술인 랩터 코드를 이용하여 네트워크 적응적 게임 영상 추출 및 전송 기술을 개발하였다. 실제 게임 영상을 이용한 시뮬레이션 결과는 제안하는 영상 기술의 효율성을 입증한다.

다수의 부스트림을 이용한 분산 비디오 스트리밍 시스템을 위한 공정하고 효율적인 부스트림 할당 기법

비디오 소스를 다수의 부스트림으로 인코딩하는 향상된 코딩 기법을 이용하는 분산 비디오 스트리밍 시스템의 경우 시스템의 용량 증대를 위해서는 피어들이 자발적으로 많은 양의 부스트림을 재전송할 수 있는 장려책이 필요하다. 또한 참여 피어들은 자원 제공자인 동시에 서비스 소비자인 특성을 가지므로 시스템의 전체 용량은 참여 피어들의 부스트림 제공량에 따라 공정하게 할당되어야 하며 시스템의 효율성 측면에서는 참여 피어들의 전체 서비스 인지 품질이 최대화 되도록 할당되어야 한다. 본 논문에서는 이와 같은 문제 해결을 위해 최적화기법을 이용한 부스트림 할당 기법을 제안한다. 제안 기법은 자원 제공자이자 소비자인 피어의 특성을 고려하여 참여 피어의 자발적 자원 제공을 장려함으로써 기존 최적화 기법과 달리 분산 비디오 스트리밍 시스템 자원의 효율적 이용과 공정한 배분을 보장한다는 것을 모의실험을 통해 정량적으로 검증하였다. In a distributed streaming system using an advanced coding scheme that encodes a video into multiple substreams, the capacity of the system depends on the amount of contribution of participating peers. Thus, an incentive mechanism for peers to contribute voluntarily is needed to increase system capacity. In addition, since peers are not only a provider but also a consumer in the system (i.e. prosumer), the overall capacity of the system must be allocated fairly among the peers while it must be allocated in a way that can maximize the net quality of experience of peers to increase system efficiency. In this paper, we propose a substream allocation method to solve the problems taking an optimization approach. Unlike the other optimization approaches, the proposed method is verified quantitatively in a simulation study that it can use the capacity of video streaming system efficiently while allocating fair amount of substreams among peers because it considers explicitly the prosumer characteristics of peers.

이종 무선망 환경에서 효과적인 영상 스트리밍 시스템

In this paper, we propose an efficient video streaming system over heterogeneous wireless networks. The proposed system modifies fountain code for the video streaming service and maximizes the target video encoding rate using multiple paths while satisfying delay and block recovery failure rate constraints of fountain code. Finally, the proposed system provides the seamless video streaming service of high quality to subscribers by dynamic adaptation of control parameters based on the states of each path over heterogeneous wireless networks.

Video streaming over P2P networks: Challenges and opportunities

A robust real-time video communication service over the Internet in a distributed manner is an important challenge, as it influences not only the current Internet structure but also the future Internet evolution. In this context, Peer-to-Peer (P2P) networks are playing an imperative position for providing efficient video transmission over the Internet. Recently, several P2P video transmission systems have been proposed for live video streaming services or video-on-demand services over the Internet. In this paper, we describe and discuss existing video streaming systems over P2P. Efficient (delay tolerant and intolerant) data sharing mechanisms in P2P and current video coding trends are elaborated in detail. Moreover, video streaming solutions (live and on-demand) over P2P from the perspective of tree-based and mesh-based systems are explained. Finally, the conclusion is drawn with key challenges and open issues related to video streaming over P2P.

A Bayesian approach for user aware peer-to-peer video streaming systems

Peer-to-Peer (P2P) architectures for live video streaming has attracted a significant attention from both academia and industry. P2P design enables end-hosts to relay streams to each other overcoming the scalability issue of centralized architectures. However, these systems struggle to provide a service of comparable quality to that of traditional television. Since end-hosts are controlled by users, their behavior has a strong impact on the performance of P2P streaming systems, leading to potential service disruption and low streaming quality. Thus, considering the user behavior in these systems could bring significant performance improvements. Toward this end, we propose a Bayesian network that captures all the elements making part of the user behavior or related to it. This network is built from the information found in a cross-analysis of numerous large-scale measurement campaigns, analyzing the user behavior in video streaming systems. We validate our model through intensive simulations showing that our model can learn a user behavior and is able to predict several activities helping thus in optimizing these systems for a better performance. We also propose a method based on traces collection of the same user type that accelerates the learning process of this network. Furthermore, we evaluate the performance of this model through exploring its applications and comparison with non-contextual models.

Robust mobile video streaming in a peer-to-peer system

In a peer-to-peer (P2P) video streaming system, peers not only consume video, but also route it to other peers in the system, where ordinary peers are assumed to have sufficient downlink speed and media capability. This assumption often fails when the P2P system consists of peers that are heterogeneous in their computing power, hardware, and media capability.In this paper, we address a problem of streaming video to mobile devices, which are less capable than ordinary peers. In order to stream video to mobile devices, transcoding is often required to render video suitable for their small display, limited downlink speed, and limited video decoding capability. However, performing transcoding at a single peer is vulnerable to peer churn, which leads to video disruption. We propose interleaved distributed transcoding (IDT), a robust video encoding scheme that allows peers more capable than mobile devices to perform transcoding in a collaborative fashion. IDT is designed in such a way that transcoded substreams are assembled into a single video stream, which can be decoded by any H.264/AVC baseline profile compliant decoder. Extensive simulations and its implementation in a real P2P system demonstrate that the proposed scheme not only reduces computational load at a peer, but also achieves robust streaming in the case of peer failure or packet loss due to adverse wireless channel conditions. We confirm this finding by analyzing the effect of distributed transcoding under peer failure.

Multi-stream 3D video distribution over peer-to-peer networks

The recent advances in stereoscopic video capture, compression, and display have made 3-dimensional (3D) video a visually appealing and costly affordable technology. There have been a series of pioneer works on streaming 3D video over the Internet. Yet the remarkably increased data volume of 3D videos poses great challenges to the conventional client/server design, which has already suffered from supporting 2D videos.In this paper, we present an initial attempt toward efficient streaming of 3D videos over a peer-to-peer network. We show that the inherent multi-stream nature of 3D video makes playback synchronization more difficult, which is particularly acute with the existence of multiple senders in a peer-to-peer overlay. We address this by a novel 2-stream 2-stage buffer design, together with weighted data scheduling and light-weight synchronization. We further discuss a series of key practical issues toward implementing our peer-to-peer 3D video streaming system, including the weight modeling for data segments, the interactions with the RTP/RTCP protocol stack, and the inter-operability with monoscopic video as well as extension to multi-view video. We have evaluated the performance of our system under different end-system and network configurations with typical 3D video streams. The simulation results demonstrate the superiority of our system in terms of both scalability and streaming quality.

Multiple description coded video streaming in peer-to-peer networks

It is known that in a peer-to-peer (P2P) network a peer node serves as both a receiver and a supplier, which enables uploading bandwidth of peer nodes to be utilized efficiently while relieving burden of the server node. This solves the scalability problem typically encountered in the traditional client–server model. However, frequent peer churn and varying bandwidth of peer nodes in P2P networks pose significant challenges for video streaming. These challenges can be addressed from both the P2P system design and the advanced video coding perspectives. In this paper, we first present a survey on the existing P2P video streaming systems that leverage the multiple description coding (MD coding or MDC) techniques, featured in providing strong error resilience for video delivery and supporting heterogeneity for peer nodes. Compared with layered coded video streaming, MD coded video streaming presents stronger robustness without requiring special provisions in P2P system design at a modest cost of compression efficiency, which is desirable in dynamic and error-prone P2P networks. In the MD coded video streaming, packet scheduling is critical to performance of mesh-based P2P systems. A new packet scheduling framework is formulated for receiver-driven MD coded video streaming, where a receiver collects peer nodes' information and generates a transmission schedule for MDC packets. In the proposed framework, a rate-distortion optimized packet selection scheme is developed to minimize the expected distortion subject to limited downloading bandwidth. Accordingly a rate-distortion based prioritized peer selection scheme is employed to choose an appropriate peer node for each of the selected packets. Simulation results validate the effectiveness of the proposed scheduling scheme and the advantage of MDC over layered coding in a network with frequent peer churn.

Quality of data delivery in peer-to-peer video streaming

QoS in a P2P video streaming system is evaluated in three stages: content generation, data delivery and video playback. We use jitter-free probability as the main performance metric to study Quality of Data delivery (QoD). A new model that incorporates both bandwidth and data availability of P2P network is proposed. Our model relies on a sharing factor that models data availability among all peers. We simulate on a minimalistic network to demonstrate how to apply the analytical model to design a P2P video streaming system with a very low jitter rate. Our simulation experimental results reveal that the lower bound on jitter-free probability is indeed effective to reflect the QoD of the entire system. Our model captures the impact of many design choices, including upload bandwidth limit, peer selection strategies, and video stream chunking schemes.

Effect of node churn on frame interval for peer-to-peer video streaming with data-block synchronization mechanism

Coolstreaming is a mesh based peer-to-peer (P2P) video streaming system in which single video stream is decomposed into multiple sub-streams. A client-peer node retrieves the sub-streams from multiple parent-peer nodes, combining them into the original video stream. Each client-peer node has two buffers, a synchronization buffer and a cache buffer, and arriving data blocks are synchronized at the synchronization buffer and then forwarded to the cache buffer. In this buffering system, data-block synchronization is important to guarantee high video quality. In this paper, we consider the effect of churn on the performance of data-block synchronization scheme with which data blocks are simultaneously forwarded just after all the data blocks composing a macro data block arrive at the synchronization buffer. It is assumed that data blocks belonging to a sub-stream arrive at the client-peer node according to an interrupted Poisson process. The synchronization buffer is modeled as a multiple-buffer queueing system with homogeneous interrupted Poisson processes, and the mean forwarding interval is derived. Numerical examples show that the average forwarding interval increases as parent-peer nodes leave more frequently.

Real-Time Fish Observation and Fish Category Database Construction

This paper proposes a distributed real-time video stream system for underwater fish observation in the real world. The system, based on a three-tier architecture, includes capture devices unit, stream processor unit, and display devices unit. It supports variety of capture source devices, such as HDV, DV, WebCam, TV Card, Capture Card, and video compression formats, such as WMV, FLV/SWF, MJPEG, MPEG-2/4. The system has been demonstrated in Taiwan for long-term underwater fish observation. CCTV cameras and high-definition cameras are deployed on our system. Video compression methods and image processing methods are implemented to reduce network transfer flow and data storage space. Marine ecologists and end users can browse these real-time video streams via the Internet to understand the ecological changes immediately. These video data is preserved to form a resource base for marine ecologists. Based on the video data, fish detection is implemented. However, it is complicated in the unconstrained underwater environment, due to the water flow causes the water plants sway severely. In this paper, a bounding-surrounding boxes method is proposed to overcome the problem. It efficiently classifies moving fish as the foreground objects and the swaying water plants as the background objects. It enables to remove the irrelevant information (without fish) to reduce the massive amount of video data. Moreover, fish tracking is implemented to acquire multiple species of fish images with varied angles, sizes, shapes, and illumination to construct a fish category database.

On Node Stability and Organization in Peer-to-Peer Video Streaming Systems

Recently, peer-to-peer video streaming technology has been widely suggested to support broadcasting videos over the Internet. Given that the application-layer nodes (peers) are autonomous and may join or leave at will. Dealing with node dynamics (known as churn) under the bandwidth and timing constraints for video streaming thus becomes a necessary yet challenging task. One conventional argument is that the stable nodes are too small a group to be effectively utilized. While we agree this argument from a whole session's point-of-view, in this paper, we argue that the significantly longer lifespans of the stable nodes allow each of them to appear in much more snapshots of the overlay than transient nodes and, as a result, they constitute a significant portion in every snapshot of the overlay, substantially affecting the performance of the overall system. Such observation has been verified by our trace analysis on PPLive, a large-scale peer-to-peer live streaming system, as well as analytical modeling based on node behaviors. Motivated by this, we further propose a tiered overlay design, with stable nodes being organized into a tier-1 backbone for serving tier-2 nodes. It offers a highly cost-effective and deployable alternative to proxy assisted designs. We develop a comprehensive set of algorithms for stable node identification and organization. Specifically, we present a novel structure, labeled tree (or LBTree in short), for the tier-1 overlay, which, leveraging stable peers, simultaneously achieves low overhead and high transmission reliability. Our tiered framework flexibly accommodates diverse existing overlay structures in the second tier. Through extensive simulations, we demonstrate that the customized optimization using selected stable nodes can greatly boost the streaming quality and also effectively reduce the control overhead.

Multi-interface Extension to a Scalable Video Streaming Architecture

Video service adaptation capabilities are essential for the efficient utilization of the network resources in heterogeneous multi-access environments and ensuring sufficient perceived service quality for the end users. Multihoming is seen as one important enabler for high-quality and reliable video streaming services and it is expected to be supported extensively in the future Internet. Already today, terminal devices are equipped with multiple network interfaces and able to use them simultaneously. In the future, mobile multimedia services such as video streaming can maximize the user experienced quality by utilizing the available network resources, concurrently. However, intelligent decision-making as well as dynamic mapping of traffic to network interfaces are required for optimal operation. In this paper, we introduce an overall architecture for adaptive video streaming exploiting the novel scalable video coding technology. We also propose a multi-interface streaming extension to the architecture to allow dynamic and concurrent usage of the available access networks in the video service delivery. We present a prototype implementation of the proposed multi-interface video streaming system and test its operation in the presence of network impairments in an experimental evaluation.

Using bandwidth aggregation to improve the performance of quality-adaptive streaming

Devices capable of connecting to multiple, overlapping networks simultaneously is becoming increasingly common. For example, most laptops are equipped with LAN- and WLAN-interface, and smart phones can typically connect to both WLANs and 3G mobile networks. At the same time, streaming high-quality video is becoming increasingly popular. However, due to bandwidth limitations or the unreliable and unpredictable nature of some types of networks, streaming video can be subject to frequent periods of rebuffering and characterized by a low picture quality.In this paper, we present a multilink extension to the data retrieval part of the DAVVI adaptive, segmented video streaming system. DAVVI implements the same core functionality as the MPEG DASH standard. It uses HTTP to retrieve data, segments video, provides clients with a description of the content, and allows clients to switch quality during playback. Any DAVVI-data retrieval extensions can also be implemented in a DASH-solution.The multilink-enabled DAVVI client divides video segments into smaller subsegments, which are requested over multiple interfaces simultaneously. The size of each subsegment is dynamic and calculated on the fly, based on the throughput of the different links. This is an improvement over our earlier subsegment approach, which divided segments into fixed size subsegments. The quality of the video is adapted based on the measured, aggregated throughput. Both the static and the dynamic subsegment approaches were evaluated with on-demand streaming and quasi-live streaming. The new subsegment approach reduces the number of playback interruptions and improves video quality significantly for all cases where the earlier approach struggled. Otherwise, they show similar performance.

Search-based composition, streaming and playback of video archive content

Locating content in existing video archives is both a time and bandwidth consuming process since users might have to download and manually watch large portions of superfluous videos. In this paper, we present two novel prototypes using an Internet based video composition and streaming system with a keyword-based search interface that collects, converts, analyses, indexes, and ranks video content. At user requests, the system can automatically sequence out portions of single videos or aggregate content from multiple videos to produce a single, personalized video stream on-the-fly.

New pixel based approach for reverse play of MPEG video for streaming system

In macroblock based architecture of MPEG video streaming system with backward playback support, the macroblocks of the frames are divided into two categories: Backward Macroblock (BMB) and Forward/Backward Macroblock (FBMB). The BMB and FBMB are processed differently. This approach reduces the network bandwidth and buffer size requirements. In this paper, we propose a pixel based approach that accesses less data from the server and hence further saves the network bandwidth and buffer requirement. The I- or P-frame (say, frame n−1) is reverse-predicted from the currently decoded frame (i.e., frame n) that is stored in the frame buffer at the client system. Using the motion vector information of frame n, the positions of its various pixels are found in the frame n−1 and their exact values are found using the prediction errors of the frame n by just subtracting them from their values in the frame n. Thus, most of the pixels of frame n−1 are predicted from the frame n. Experimental results show that on an average 93.4% of pixels in the previous I- or P-frame can be reverse-predicted from the current P-frame. The rest 6.6% unpredicted pixels are accumulated in the form of blocks and those blocks are requested from the server. We also propose new Block Identification Algorithms to identify different blocks of unpredicted pixels in an image. They are Maximum Height Minimum Width (MHMW), First Come First Serve (FCFS), Maximum Area (MA), and Biggest Block (BB) algorithms. The server processes the MPEG video stream and returns the desired blocks. We also discuss a FindBlock algorithm for extracting a small block of any frame from the MPEG video stream. Thus, only the motion vectors, prediction errors of frame n, and the unpredicted pixels of the frame n−1 need to be transmitted to the client system. This makes considerable saving in system resources.

An effective mesh-pull-based P2P video streaming system using Fountain codes with variable symbol sizes

In this paper, we propose an effective mesh-pull-based video streaming system over P2P networks using Fountain codes with variable symbol sizes for video-on-demand services. The goal of the proposed system is to provide a stable video streaming service of high quality with minimum computational complexity and a short initial latency over P2P networks. Basically, Fountain codes are adopted in the proposed system to simplify the handshaking procedure, which causes a large initial latency, and to support a robust video streaming service despite packet losses. The proposed Fountain encoding mechanism works by using feedback information to reduce unnecessary encoded symbol generation. In addition, the Fountain code symbol size is continuously adjusted to minimize additional computational overhead required for Fountain encoding/decoding. The proposed system is fully implemented in software and examined over an Internet environment.

Queueing analysis of data block synchronization mechanism in peer-to-peer based video streaming system

In a Peer-to-Peer (P2P) based video streaming system such as Coolstreaming, a single video stream is decomposed into multiple sub-streams. A client-peer node receives the sub-streams from multiple parent-peer nodes, combining them into the original video stream. Each client-peer node has a synchronization buffer and a cache buffer. Data blocks are stored in the synchronization buffer in a sub-stream basis, and then forwarded into the cache buffer according to their sequence numbers. In this buffering system, data-block synchronization plays a crucial role to guarantee video quality. In this paper, we consider the performance of data-block synchronization scheme with which data blocks are simultaneously forwarded just after all the data blocks composing a macro data block arrive at the synchronization buffer. We model the synchronization buffer as a multiple-buffer queueing system with homogeneous Poisson arrival processes, deriving the mean forwarding interval. We also consider the frame loss probability for multiple-path video streaming, investigating how the number of sub-streams decreases the frame loss probability. Numerical examples show that increasing the number of sub-streams makes the average forwarding interval large, while the frame loss probability at the bottleneck router is improved. It is also shown that increasing the synchronization buffer decreases the average forwarding interval.