Enabling broadcast of user-generated live video without servers

We are witnessing the unprecedented popularity of User-Generated-Content (UGC) on the Internet. While YouTube hosts pre-recorded video clips, in near future, we expect to see the emergence of User-Generated Live Video, for which any user can create its own temporary live video channel from a webcam or a hand-held wireless device. Hosting a large number of UG live channels on commercial servers can be very expensive. Server-based solutions also involve various economic, copyright and content control issues between users and the companies hosting their content. In this paper, leveraging on the recent success of P2P video streaming, we study the strategies for end users to directly broadcast their own live channels to a large number of audiences without resorting to any server support. The key challenge is that end users are normally bandwidth constrained and can barely send out one complete video stream to the rest of the world. Existing P2P streaming solutions cannot maintain a high level of user Quality-of-Experience (QoE) with such a highly constrained video source. We propose a novel Layered P2P Streaming (LPS) architecture, to address this challenge. LPS introduces playback delay differentiation and constructs virtual servers out of peers to boost end users’ capability of driving large-scale video streaming. Through detailed packet-level simulations and PlanetLab experiments, we show that LPS enables a source with upload bandwidth slightly higher than the video streaming rate to stream video to tens of thousands of peers with premium quality of experience.     

Adaptive topology formation for peer-to-peer video streaming

In this paper we propose an adaptive P2P video streaming framework to address the challenges due to bandwidth heterogeneity and peer churn on the Internet. This adaptive streaming framework consists of two major components, source rate adaptation and adaptive overlay topology formation, to maximize the video quality and fully utilize the overall peer upload capacity. In the source rate adaptation, the video server adapts the video source rate automatically based on the local measurement of peers’ download rates, so that the P2P network is not overloaded beyond its bandwidth capacity and peers are able to achieve smooth video playback. To combat bandwidth heterogeneity, we propose to construct a desirable link-level homogeneous overlay topology using a Markov chain Monte Carlo method, so that peers achieve an equal per-connection upload/download bandwidth. In this link-level homogeneous network, video flows do not encounter any bottlenecks along the delivery paths, and peers achieve high download rates to ensure smooth video playback. We also design a fully distributed algorithm to implement the dual mechanisms of the adaptive topology formation and the source rate maximization. To evaluate the performance of our streaming framework, we conduct both mathematical analysis and extensive simulations. The simulation results confirm our analysis and show that the proposed distributed algorithm is able to maximize the video playback quality with fast convergence.     

A comprehensive study of the use of advertisements as incentives in P2P streaming systems

P2P streaming systems, such as PPLive and PPStream, have become popular services with the widespread deployment of broadband networks. However, P2P streaming systems still face free-riding problems, similar to those that have been observed in P2P file sharing systems. Thus, one important problem in providing streaming services is that of providing appropriate incentives for peers to contribute their upload capacity. To this end, we propose the use of advertisements as an incentive for peers to contribute upload capacity. In the proposed framework, peers enjoy the same quality of streamed media, with the difference in quality of service being achieved through different amounts of advertisements viewed, based on the resource contributions to the system. Moreover, since calculating peers’ contributions accurately is important to successfully deploying such systems, we design a token-based framework to address this problem. An extensive simulation-based study is performed to evaluate the proposed approach. The results demonstrate that our approach provides appropriate incentives for peers to contribute their resources. Furthermore, we explore several characteristics of the token-based mechanism which can provide system developers with insight into efficient development of such systems.     

Adaptive,incentive and scalable dynamic tree overlay for P2P live video streaming

In this paper, we propose a new multicast tree framework to be used in peer-to-peer (P2P) live video streaming systems. The proposed system, adapts the tree links under high peer churn and runs in a totally distributed manner. In order to provide this dynamism and seamless streaming at the same time, we propose a cross layer design involving scalable video codec, backup parents and hierarchical clusters. The performance of the system is measured in real world environment PlanetLab that has nodes distributed all over the world. The experiments show that the proposed system provides high quality of experience (QoE) in terms of Peak Signal to Noise Ratio (PSNR), playback delay and duration of pauses. The proposed system also provides incentive mechanism to its users.     

User density sensitive P2P streaming in wireless mesh networks

Link rate allocation is very important for supporting high video playback rate in Peer-to-Peer video streaming. Although many studies can be found on resource allocation in P2P streaming in wired networks, very few studies have studied the problem in wireless networks, especially in Wireless multi-hop Mesh Networks (WMNs), which is still challenging. To maximize the users’ satisfaction of P2P streaming in WMNs, this paper focuses on link rate allocation problem and proposes a fully distributed algorithm to efficiently utilize the upload and download bandwidth of wireless mesh nodes. We first build an efficient P2P streaming system based on the experimental results from real deployment of our wireless mesh testbed. Then we design an efficient distributed algorithm based on the solution to a linear optimization model, which optimizes towards a user-density-related objective to decide the best streaming rates among peers. Our scheme is resilient to network dynamics that is characteristic in wireless multi-hop peer-to-peer networks. The simulation experiments demonstrate the significant performance enhancement by using the proposed rate allocation algorithm in WMNs.     

支持高视频播放率的层次化P2P流媒体系统

目前的P2P流媒体系统具有自组织、容错性和匿名性等优点,但是在健壮性和对高视频播放率的有效支持方面还存在一些问题。本文提出了一种层次化P2P流媒体系统(HPSS)来支持高视频播放率,节点根据带宽和延迟分组聚类,在系统中形成多级层次结构,从视频源服务器来取得视频数据。通过积极地平衡聚类中的上传能力,既能够有效地解决P2P系统中支持高视频播放率的问题,提供接近一个P2P系统能够达到的最大流媒体速率,同时保证系统具有良好的健壮性,在聚类的头节点失效的情况下,不降低整个系统的流媒体速率。最后通过仿真实验证明了HPSS的上述优点。     

The interleaved video frame distribution for P2P-based VoD system with VCR functionality

The peer-to-peer (P2P) network structure is widely employed for video streaming applications because of its high stability, flexible extensibility, and ability to distribute data stream loading among different peer nodes. Numerous P2P schemes have been proposed for video on demand (VoD) applications. High video source searching cost and long response latency are always issues in dealing with VCR functionality, such as jump and fast-forward/rewind, because of asynchronous interactive and random join/leave behaviors of end users. To overcome this bottleneck, an interleaved video frame distribution (IVFD) scheme is proposed to support full VCR functionality in a P2P environment without searching for new sources. Instead of acquiring video stream data from a single parent peer in the published schemes, each child peer in the IVFD scheme can simultaneously acquire interleaved video data from multiple parent peers. When a client peer carries out arbitrary VCR operations, such as jump or fast-forward/rewind, its parent peers are still able to provide intermittent video stream data for the client peer; thus, no video source search is necessary. Simulation results reveal excellent load distribution performance and response latency for VCR operations in the proposed IVFD scheme.     

LayerP2P: Using Layered Video Chunks in P2P Live Streaming

Although there are several successful commercial deployments of live P2P streaming systems, the current designs; lack incentives for users to contribute bandwidth resources; lack adaptation to aggregate bandwidth availability; and exhibit poor video quality when bandwidth availability falls below bandwidth supply. In this paper, we propose, prototype, deploy, and validate LayerP2P, a P2P live streaming system that addresses all three of these problems. LayerP2P combines layered video, mesh P2P distribution, and a tit-for-tat-like algorithm, in a manner such that a peer contributing more upload bandwidth receives more layers and consequently better video quality. We implement LayerP2P (including seeds, clients, trackers, and layered codecs), deploy the prototype in PlanetLab, and perform extensive experiments. We also examine a wide range of scenarios using trace-driven simulations. The results show that LayerP2P has high efficiency, provides differentiated service, adapts to bandwidth deficient scenarios, and provides protection against free-riders.     

Measurement study on P2P streaming systems

Originally used as the default infrastructure for efficient file sharing, peer-to-peer (P2P) architecture achieved great successes. Now, the P2P model has been adopted for many other distributed applications, such as instant message and phone services, Internet gaming, and large-scale scientific computing. In recent years, P2P streaming systems experienced tremendous growth and became one of the largest bandwidth consumers on the Internet. Compared to standard file sharing systems, the streaming services show unique characteristics with more stringent time constraints and require much higher network bandwidth. It is extremely important to evaluate and analyze existing applications, and investigate the merits and weaknesses in these systems for future development. In this paper, we conduct a comprehensive measurement study on two of the most popular P2P streaming systems, namely, PPLive and PPStream. They are very popular P2P streaming applications, and serving millions of registered users with hundreds of live TV channels and millions of other video clips. In our measurement, we deploy our collectors in China, and both live TV and video-on-demand (VoD) channels are evaluated. We record run-time network traffic on the client side, compare and analyze the characteristics of these channels based on their popularity. For both categories, we perceive that, in general, the two measured P2P streaming systems provide satisfactory experience to the audiences for all channels regardless of popularity. However, the most of data are downloaded from the dedicated servers for unpopular channels. We also observe that live TV channels show better peer coordination than VoD channels. Beside the traffic, we have also collected cache replacement information for VoD channels, and these measurement results can help us understand the caching mechanism of P2P streaming systems. With the support of the cache, VoD channels perform better than their counterparts in the live TV category in terms of data transmission, workload distribution, and signal traffic overhead. Overall, our results reveal that although P2P streaming systems can usually provide excellent viewing experience for popular channels, there are still challenges to fully support unpopular channels. New designs and algorithms are in urgent need, especially for unpopular live TV channels.     

Hierarchically Clustered P2P Video Streaming: Design,implementation, and evaluation

P2P based live streaming has been gaining popularity. The new generation P2P live streaming systems not only attract a large number of viewers, but also support better video quality by streaming the content at higher bit-rate. In this paper, we propose a novel P2P streaming framework, called Hierarchically Clustered P2P Video Streaming, or HCPS, that can support the streaming rate approaching the optimal upper bound while accommodating large viewer population. The scalability comes with the hierarchical overlay architecture by grouping peers into clusters and forming a hierarchy among them. Peers are assigned to appropriate cluster so as to balance the bandwidth resources across clusters and maximize the supportable streaming rate. Furthermore, individual peers perform distributed queue-based scheduling algorithms to determine how to retrieve data chunks from source and neighboring peers, and how to utilize its uplink bandwidth to serve data chunks to other peers. We show that queue-based scheduling algorithms allow to fully utilize peers’ uplink bandwidths, and HCPS supports the streaming rate close to the optimum in practical network environment. The prototype of HCPS is implemented and various design issues/tradeoffs are investigated. Experiments over the PlanetLab further demonstrate the effectiveness of HCPS design.     

Practical design of a proxy agent to facilitate adaptive video streaming service across wired/wireless networks

Thanks to the growing of the wireless networks, the video streaming application becomes a ubiquitous joyful service. In a wireless communication network environment, the service traffic spans across the wired and wireless domains. In this article, we propose a practical design of a proxy agent - SPONGE (Stream Pooler Over a Network Graded Environment) sitting between the wireless User Equipments (UEs) and the video streaming server to facilitate the adaptive video streaming service across wired/wireless networks. To make the wireless streaming service more efficient, an input video session would be encoded as multiple qualities of video streams so that UEs with a similar receiving condition can share streams with the same service quality via SPONGE. SPONGE can alleviate the direct load on the original stream broadcasting server. Meanwhile, it can make each UE get an adaptive streaming service according to the network conditions of the UE by a reduced network condition feedback latency. Our theoretical analysis and simulation results show that SPONGE can help wireless streaming users get a smooth and better playback quality by a quick and accurate reaction to the network condition.     

一种基于P2P的视频点播系统设计

在计算机发展领域中,目前有一项新兴的技术———视频点播技术(VOD),它是一种根据观众的要求播放节目的系统,随时提供交互式视频服务,主要用于实现多用户对网络多媒体文件的共享播放。文中将P2P与Internet上重要的媒体传输技术———流媒体技术相结合提出了一个基于P2P的视频点播系统的具体设计与实现方案,讨论了系统设计和实现过程中采用的相关技术与方法,采用点组技术,重点提出了一种新的发现机制。     

An efficient scheduling algorithm for scalable video streaming over P2P networks

During recent years, the Internet has witnessed rapid advancement in peer-to-peer (P2P) media streaming. In these applications, an important issue has been the block scheduling problem, which deals with how each node requests the media data blocks from its neighbors. In most streaming systems, peers are likely to have heterogeneous upload/download bandwidths, leading to the fact that different peers probably perceive different streaming quality. Layered (or scalable) streaming in P2P networks has recently been proposed to address the heterogeneity of the network environment. In this paper, we propose a novel block scheduling scheme that is aimed to address the P2P layered video streaming. We define a soft priority function for each block to be requested by a node in accordance with the block’s significance for video playback. The priority function is unique in that it strikes good balance between different factors, which makes the priority of a block well represent the relative importance of the block over a wide variation of block size between different layers. The block scheduling problem is then transformed to an optimization problem that maximizes the priority sum of the delivered video blocks. We develop both centralized and distributed scheduling algorithms for the problem. Simulation of two popular scalability types has been conducted to evaluate the performance of the algorithms. The simulation results show that the proposed algorithm is effective in terms of bandwidth utilization and video quality.     

P2P流媒体技术飞速发展

P2P流媒体技术,也称为对等网络(peer-to-peer)技术,简单地说,就是一种用户不经过中继设备直接交换数据或服务的技术。它将目前互联网的"内容位于中心"模式改变为"内容位于边缘"模式,将权利交还给用户。在这种架构中,每个节点的地位都相同,具备客户端和服务器的双重特性,可以同时作为服务使用者和服务提供者。该文将为读者讲述在P2P流媒体技术的原理以及应用,希望能使大家对这种现阶段应用广泛,发展迅速的流媒体技术有一定的了解。     

A token-based incentive mechanism for video streaming applications in peer-to-peer networks

Free-riding is one of the main challenges of Peer-to-Peer (P2P) streaming systems which results in reduction in video streaming quality. Therefore, providing an incentive mechanism for stimulating cooperation is one of the essential requirements to maintain video Quality of Experience (QoE) in such systems. Among the existing mechanisms, payment-based schemes are most suitable for streaming applications due to their low overhead. However, to date, no dynamic payment mechanism has been proposed which can take the stochastic dynamics of the video streaming ecosystem (e.g., the request arrival, demand submission, bandwidth availability, etc.) into account. In this paper, we propose a dynamic token-based payment mechanism in which each peer earns tokens by admitting other peers’ requests and spends tokens for submitting its demands to the others. This system allows the peers to dynamically adjust their income level in adaptation to changes in the system state. We propose a Constrained Markov Decision Process (CMDP) formulation in which the goal of each peer is to obtain a request admission policy which minimizes the expected cumulative cost of consumed bandwidth, while satisfying a long-term constraint on the Mean Opinion Score (MOS) of the users as the measure of QoE. The proposed admission policy is adaptive to the request arrival process, bandwidth state and the token bucket length of each peer. To make up for the lack of design-time knowledge of the system’s statistics, each individual peer is equipped with a model-free algorithm to learn its optimal admission policy over the course of real-time interaction with the system. Simulation results are presented to compare the performance of the proposed algorithm against baseline schemes such as: random, token-threshold, bandwidth-threshold and myopic algorithms.     

Modeling and evaluating IPTV applications in WiMAX networks

Internet Protocol-based Television (IPTV) is a digital television service which delivers television content via an IP network. The rapid growth of wireless network technology in recent years has changed, the way people access the Internet. Adding mobility to IPTV can create a truly compelling ubiquitous service which spans different network domains and varied IP-enabled terminals and devices, such as set-top boxes, PCs and cell phones. However, extending IPTV service to wireless networks requires overcoming bandwidth bottlenecks and high packet loss rates. Following the IEEE 802.16 standard, worldwide interoperability for microwave access (WiMAX) features high data rates and large service coverage, offering a wireless broadband solution for IPTV services. While previous research has focused on creating a broadband IPTV service few studies have practically evaluated IPTV applications in a wireless broadband network environment. In this paper, we model and evaluate a common constant bit rate (CBR)¹ based IPTV application and an IPTV live streaming (PPStreaming)² application while retrieving IPTV content via a WiMAX network. We also use the NS2 simulation tool to evaluate the performance of these two IPTV applications. The evaluation metrics include latency, packet loss, data rate and throughput statistics when the two IPTV applications are run in the WiMAX network. ¹The simplest IPTV solution is to convey video content by CBR. IPTV operators and content delivery networks relay CBR streaming content to control the demand for network capacity. Broadcasters prefer CBR video as it conserves bandwidth resources, but CBR delivery can degrade video quality result in higher overall demand on network capacity. ²PPStreaming (also referred to as P2P streaming Internet TV) is a network for live media streaming. In principle it’s similar to BitTorrent (BT) in that it provides stable and smooth broadcast of TV programs to broadband users. Unlike traditional streaming media, PPStreaming adopts P2P-streaming technology and supports full-scale visits with tens of thousands of simultaneous users. Its client software can be used in the browser or as a standalone executable.     

ORN: A content-based approach to improving supplier discovery in P2P VOD networks

There are two major building blocks in operating a peer-to-peer (P2P) video-on-demand (VOD) network: supplier discovery and content delivery. Supplier discovery concerns the discovery of peer nodes in the network that can provide the streaming data blocks needed for playing by a local node. The more suppliers one can discover, the higher the chance of locating quality suppliers for delivering contents smoothly to ensure uninterrupted playback. The key to supplier discovery is to establish and track the supply-demand relationship among the peers. For P2P VOD, the supply-demand relationship is determined by the buffer contents of the peers. Unfortunately, the buffer contents change rapidly as peers play the video, especially under VCR operations. The challenge is to track all the dynamic relationships in an efficient way. In this paper, we propose an Overlapping Relation Network (ORN). The idea is to track the dynamic supply-demand relationship by tracking the overlapping of peers’ buffer contents. As long as peers play the video at the same rate, the overlapping relationship is stable and can be used for low-cost supplier discovery. Extensive analyses and simulation experiments show that in most cases the ORN can discover more than 96% of the suppliers in the network, resulting in a streaming continuity that is superior to that of other approaches.     

A P2P streaming architecture supporting scalable media

Peer-to-peer (P2P) streaming solutions are changing the way real-time multimedia transmission is distributed over the Internet. The advances in video coding, like Scalable Video Coding, also turns possible high-quality/definition video distribution and consumption. The recent push in using the standard HTTP protocol for streaming videos in the World Wide Web, is also making converged entertainment services come closer to global deployment across TV, Tablet and mobile devices. The combination of Scalable Video, P2P networks and Web technologies for transmitting high-quality live and time-shifted media contents, is a potential area of innovation and a very actual research topic. This paper describes the architecture of a quality-centric P2P distribution network supporting adaptive and scalable streamable media, that decouples the transport mechanisms from the media content type and structure (video, audio, timed-data, timed-text), irrespective of their encoding schemes. The set of P2P streaming protocols designed for the network enables streaming of live and on-demand media, with very low signaling cost. Prototypes of the P2P network components were implemented and integrated in the streaming platform of EU FP7 SARACEN Project. A suite of tests for evaluation of the performance of the solution demonstrates that it keeps a fairly stable quality level with reduced amplitude and frequency of variations, raising the overall quality perceived by the end-user.     

视频流自适应传输技术研究

对当前视频流技术所采取的各种压缩算法及标准、传输协议、拥塞控制等技术进行了总结与分析，在此基础上对IP网络上的视频流自适应传输技术进行了研究，建立了实现该技术的框架。此技术框架综合了实时的视频自适应编码技术和有效的带宽自适应传输技术。实验结果表明，在对视频流的实时性要求高的应用上具有较突出的优势。     

Redesigning multi-channel P2P live video systems with View-Upload Decoupling

In current multi-channel P2P live video systems, there are several fundamental performance problems including exceedingly-large channel switching delays, long playback lags, and poor performance for less popular channels. These performance problems primarily stem from two intrinsic characteristics of multi-channel P2P video systems: channel churn and channel-resource imbalance. In this paper, we propose a radically different cross-channel P2P streaming framework, called View-Upload Decoupling (VUD). VUD strictly decouples peer downloading from uploading, bringing stability to multi-channel systems and enabling cross-channel resource sharing. We propose a set of peer assignment and bandwidth allocation algorithms to properly provision bandwidth among channels, and introduce substream-swarming to reduce the bandwidth overhead. We evaluate the performance of VUD via extensive simulations as well with a PlanetLab implementation. Our simulation and PlanetLab results show that VUD is resilient to channel churn, and achieves lower switching delay and better streaming quality. In particular, the streaming quality of small channels is greatly improved.