一种分层P2 P流媒体系统重叠网的构建策略

基于Peer-to-Peer(P2P)技术的流媒体应用具有部署效率高及可扩展性好等突出优势。而采用分层视频编码技术的P2P流媒体系统把原视频流分解为多个视频层数据进行分发,让节点能够选择与自己带宽资源相匹配的视频质量,使其很好地适应节点的异构性。但是各分层视频数据传输的路径存在较大差异,使重叠网构建策略面临更大的挑战。因此定义了基于分层视频编码技术环境下的P2P流媒体重叠网络构建问题,并证明该问题是一个NP难问题。提出了一种构建重叠网的集中启发式算法,同时还提出了一种基于视频组(Streaming Group)的分布式重叠网络构建策略。通过大规模网络仿真实验验证了基于该分布式重叠网构建策略的分层流媒体系统具备低服务器带宽占用、高数据获取率等优点。     

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.     

累计分层P2P流媒体数据分配算法*

提出接收者驱动的面向启动时间的数据包分配算法（cumulative layered streaming packet assignment algorithm,CLSPA）,该算法使媒体服务质量指标中的服务启动时间（媒体数据块开始传输与在接收点连续播放该数据块之间的缓冲延迟）得到优化,同时保证动态环境流媒体的播放质量。仿真实验表明,CLSPA与其他算法相比,在服务启动时间和服务质量方面能获得更佳的分配结果。     

Scalable playback rate control in P2P live streaming systems

Current commercial live video streaming systems are based either on a typical client–server (cloud) or on a peer-to-peer (P2P) architecture. The former architecture is preferred for stability and QoS, provided that the system is not stretched beyond its bandwidth capacity, while the latter is scalable with small bandwidth and management cost. In this paper, we propose a P2P live streaming architecture in which by adapting dynamically the playback rate we guarantee that peers receive the stream even in cases where the total upload bandwidth changes very abruptly. In order to achieve this we develop a scalable mechanism that by probing only a small subset of peers monitors dynamically the total available bandwidth resources and a playback rate control mechanism that dynamically adapts playback rate to the aforementioned resources. We model analytically the relationship between the playback rate and the available bandwidth resources by using difference equations and in this way we are able to apply a control theoretical approach. We also quantify monitoring inaccuracies and dynamic bandwidth changes and we calculate dynamically, as a function of these, the maximum playback rate for which the proposed system able to guarantee the uninterrupted and complete distribution of the stream. Finally, we evaluate the control strategy and the theoretical model in a packet level simulator of a complete P2P live streaming system that we designed in OPNET Modeler. Our evaluation results show the uninterrupted and complete stream delivery (every peer receives more than 99 % of video blocks in every scenario) even in very adverse bandwidth changes.     

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.     

Churn-aware optimal layer scheduling scheme for scalable video distribution in super-peer overlay networks

To model a layered video streaming system in super-peer overlay networks that faces with heterogeneity and volatility of peers, we formulate a layer scheduling problem from understanding some constraints such as layer dependency, transmission rule, and bandwidth heterogeneity. To solve this problem, we propose a new layer scheduling algorithm using a real-coded messy genetic algorithm, providing a feasible solution with low complexity in decision. We also propose a peer-utility-based promotion algorithm that selects the most qualified neighbor to guarantee the sustained quality of streaming despite high intensity of churn. Simulation results show that the proposed layer scheduling scheme can achieve the most near-optimal solutions compared to the four conventional scheduling heuristics in the average streaming ratio. It also highly outperforms those with different peer selection strategies in terms of the average bandwidth (6.9 % higher at least) and the variation of utilization (11.3 % lower at least).     

一种分阶段的P2P流媒体数据调度算法

针对当前P2P流媒体中各节点数据调度时独立获取数据而对提高节点间数据协作性考虑不足,导致服务器负载较重的问题,提出一种分阶段的数据调度算法。当多个节点将请求的数据中含有相同数据块时,各节点将分两个阶段合作的获取这些数据。第1阶段按照带宽相对大小各节点以合作的方式先各自获取数据的一个子集,第2阶段节点间再充分共享上一阶段已经获得的子集数据,协作地完成该轮调度的数据传输。仿真实验表明该算法可以提高节点间数据协作性,充分利用节点带宽资源传输媒体数据,提高系统可扩展性。     

InstantLeap: an architecture for fast neighbor discovery in large-scale P2P VoD streaming

In large-scale peer-to-peer (P2P) video-on-demand (VoD) streaming applications, a fundamental challenge is to quickly locate new supplying peers whenever a VCR command is issued, in order to achieve smooth viewing experiences. For many existing commercial systems which use tracker servers for neighbor discovery, the increasing scale of P2P VoD systems has overloaded the dedicated servers to the point where they cannot accurately identify the suppliers with the desired content and bandwidth. To avoid overloading the servers and achieve instant neighbor discovery over the self-organizing P2P overlay, we design a novel method of organizing peers watching a video. The method features a light-weight indexing architecture to support efficient streaming and fast neighbor discovery at the same time. InstantLeap separates the neighbors at each peer into a streaming neighbor list and a shortcut neighbor list, for streaming and neighbor discovery respectively, which are maintained loosely but effectively based on random neighbor list exchanges. Our analysis shows that InstantLeap achieves an O(1) neighbor discovery efficiency upon any playback “leap” across the media stream in streaming overlays of any size, and low messaging costs for overlay maintenance upon peer join, departure, and VCR operations. We also verify our design with large-scale simulation studies of dynamic P2P VoD systems based on real-world settings.     

SmartPeerCast: a Smart QoS driven P2P live streaming framework

The P2P swarm technologies have been shown to be very efficient for medium scale content distribution systems in the last few years, such as the file sharing and video-on-demand (VOD) applications. However it is still an open topic about how to deploy the P2P paradigm for the real time video broadcasting (RTVB) applications. The P2P RTVB application is different from the cache based P2P system because it has more stringent restrictions for startup time and packet loss ratio. In this paper, an adaptive media broadcasting P2P framework named SmartPeerCast which employs the media transrating service to control the quality of service (QoS), is proposed. SmartPeerCast achieves a network awareness, codec awareness, and high performance RTVB service with four key designs: (1) It groups the newly joined peers into different quality clusters by their uploading capability. This clustering mechanism avoids the bandwidth bottleneck between the heterogeneous peers of the overall P2P overlay by only forwarding the same quality stream over the peers in the same cluster. (2) The streaming quality is adjusted adaptively between the sending and the receiving peers by a Smart QoS algorithm to compensate for the network jitters to reduce the receiving peer’s playback jitter. (3) The receiving peer monitors the data forwarding QoS of the sending peer to select the best suitable parent node dynamically. The SmartPeerCast uses this Smart QoS framework to implement an incentive mechanism to award the peers with high uploading contributions by migrating them to a higher quality cluster. (4) A transrating engine is used at the leaf nodes of the high quality cluster to forward the stream with suitable bits rate to the nodes of the low quality cluster; this transrating service not only can fully utilize the uploading bandwidth of the peers in the higher quality cluster but also avoids the bandwidth bottleneck of stream forwarding between the heterogeneous peers. Our experiment results and the real deployment show that SmartPeerCast can eliminate the bandwidth bottleneck and content bottleneck between the heterogeneous peers with a smaller startup time and packet loss and it is a high performance and medium scale P2P RTVB framework.     

基于P2P的用户生产内容视频资源查找策略

现有用户生产内容(UGC)类视频系统通常采用C/S架构设计,导致了视频服务器极大的带宽压力。提出一种采用对等网(P2P)的在线短视频查找策略——FastSearch,其目的是利用视频资源之间的关联关系进行视频资源定位,以显著提高点播节点之间的视频分享效率并降低对视频服务器的带宽需求。实验表明FastSearch具备良好的视频数据源节点查找能力,集成了该查找策略的短视频系统能有效减少对视频服务器的带宽消耗。     

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 platform to manage peer churn and bandwidth fluctuations in real-time multimedia P2P networks

In the last few years, new service providers are growing in the Internet scenario to create new multimedia services. The most common approach to this end is based on peer-to-peer (P2P) networks. The new service providers are manifesting great interest not only for classical multimedia applications, like video streaming and video on demand, but also for multi-party games, private video-chat rooms, videoconference and real-time video teaching, usually containing a small number of high-interactive group members. The target of this paper is to define a multipoint multimedia communication platform for such kind of applications, accounting both peer set variation (peer arrivals and departures) and peer bandwidth modifications. In addition, a revenue model for providers of this kind of services is proposed to allow them to design their networks in order to maximize their revenue while satisfying user requirements in terms of both admission rejection probability and perceived quality on the received video stream.     

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.     

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.     

Hybrid fluid modeling approach for performance analysis of P2P live video streaming systems

In this paper a hybrid modeling approach with different modeling formalisms and solution methods is employed in order to analyze the performance of peer to peer live video streaming systems. We conjointly use queuing networks and Fluid Stochastic Petri Nets, developing several performance models to analyze the behavior of rather complex systems. The models account for: network topology, peer churn, scalability, peer average group size, peer upload bandwidth heterogeneity and video buffering, while introducing several features unconsidered in previous performance models, such as: admission control for lower contributing peers, control traffic overhead and internet traffic packet loss. Our analytical and simulation results disclose the optimum number of peers in a neighborhood, the minimum required server upload bandwidth, the optimal buffer size and the influence of control traffic overhead. The analysis reveals the existence of a performance switch-point (i.e. threshold) up to which system scaling is beneficial, whereas performance steeply decreases thereafter. Several degrees of degraded service are introduced to explore performance with arbitrary percentage of lost video frames and provide support for protocols that use scalable video coding techniques. We also find that implementation of admission control does not improve performance and may discourage new peers if waiting times for joining the system increase.     

Joint bandwidth allocation,data scheduling and incentives for scalable video streaming over peer-to-peer networks

The overall performance of a peer-to-peer (P2P) scalable streaming system largely depends on the strategies employed in bandwidth allocation, data scheduling and incentives. In this paper, we develop a credit-based content-aware bandwidth auction model for scalable streaming in P2P networks. It formulates multi-overlay multi-layer bandwidth request and allocation problems as auction games. Each peer in the games acts as both auctioneer and player. Being a auctioneer, it maximizes the total revenue (credits) by selling upload bandwidth; Being a player, it uses the credits earned in bandwidth sales to sequentially bid for layer bandwidth so as to maximize the received video quality. Also, a content-aware bidding strategy is proposed, under which the required bandwidth quantity from a peer is determined by the informative video chunks and the marginal net utility that peer could provide, as well as the available credits and the maximum layer bit rate. The convergence of the proposed auction algorithm is mathematically proved. Finally, the performance of the proposed scheme is verified by simulation results.     

A P4P-integrated data-driven P2P system for the live multimedia streaming service

The Proactive network Provider Participation for the P2P (P4P) architecture deploys central servers, which perceives network status and provides peering suggestions to P2P systems in order to achieve better network resource utilization while supporting best possible application performance. However, P4P alone may not be able to make appropriate peering suggestions for live multimedia streaming since it does not include mechanisms to reflect some of the parameters that are important to the QoS of live multimedia streaming such as upload bandwidth and stability of a peer as a stream deliverer. Furthermore, peer synchronization and parent replacement in the middle of a session, which are critical issues to the QoS of live multimedia streaming, are also left as the matters to be dealt with by the P2P systems alone. Most of the existing data-driven P2P systems leverage periodic information exchanges among neighboring peers in order to cope with these problems, which may incur long delay and high control overhead. In this paper, we proposed P4P-integrated data-driven P2P system for live multimedia streaming service. The proposed system includes not only the peering suggestion mechanism appropriate for live multimedia streaming but also the peer synchronization and parent replacement mechanisms, which exploit the centralized P4P framework and do not require periodic control information exchanges. We implemented the system in NS-2 simulator and compared its performance to the P4P and existing data-driven P2P systems. The results from experiments show that the proposed system enhances QoS compared to the existing data-driven P2P systems while maintaining the same level of network efficiency of the original P4P.     

WuKong: a practical video streaming service based on native BitTorrent and scalable video coding

Many researches on peer-to-peer video streaming have focused on dealing with highly dynamic, high-churn P2P environment. Most of P2P streaming protocols were modified from a P2P file sharing protocol. Inspired by the high performance on peer-to-peer file sharing of BitTorrent, we propose an overlaying streaming mechanism on the native BitTorrent protocol and realize a practical P2P video streaming service, called WuKong. WuKong not only takes advantages of BitTorrent but also combines the video scalability of layered video coding. In this paper, we depict an overlaid streaming mechanism in WuKong and an adaptive layer-downloading process to balance between the video quality and bandwidth utilization on heterogeneous peers. WuKong is carried out by using an open-sourced library of the BitTorrent protocol, coding schemes of the Windows Media Video (WMV), and the Scalable Video Coding (SVC). We measured and compared the service quality of end-users served by WuKong on heterogeneous peers. In addition, we evaluated the effectiveness of WuKong with peers that are randomly joining and leaving the P2P network. The results show that WuKong not only provides high quality P2P video streaming services but also supports different scaling abilities over heterogeneous devices.