Modelling and analysis of non-cooperative peer-assisted VoD streaming in managed networks

The growing popularity of the Video on Demand service in the Internet Protocol Television environments and the demand for increased quality of the offered videos are becoming a serious threat for the service providers because the high amounts of video traffic are causing congestion in the delivery networks. One of the most acceptable approaches to solve this issue is the peer-assisted streaming, where the peers participate in the streaming process in order to alleviate the load on the streaming servers and in the core of the network. Although the reliability of the Peer-to-Peer service is considerably improved in the managed networks because of the control that the operators have over the clients’ Set-Top Boxes, the failures of the peers still cannot be completely eliminated. The operator can take advantage of the streaming and storage resources of the clients and use them for peer-assisted streaming only while they are watching a video, but not after they finish the streaming session because they may turn off their receiving devices until the next session. In this chapter, we address the issue of the failures of the peers in such environments and their influence on the traffic requested from the servers for providing uninterrupted video experience. For that purpose, we propose a precise mathematical tool for modelling a peer-assisted system for Video on Demand streaming in managed networks with non-cooperative peers, which may decide not to share their resources while they are not active. This tool calculates the performance of the system taking into consideration large variety of system parameters, including the failure probability and the time the peers spend until they decide to turn on the STB and join the network. As the results from the simulations verify the correctness of the mathematical model, we use it to analyse how the failures of the peers are affecting the system’s performance for different system parameters.     

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。     

Dynamic Bandwidth Auctions in Multioverlay P2P Streaming with Network Coding

In peer-to-peer (P2P) live streaming applications such as IPTV, it is natural to accommodate multiple coexisting streaming overlays, corresponding to channels of programming. In the case of multiple overlays, it is a challenging task to design an appropriate bandwidth allocation protocol, such that these overlays efficiently share the available upload bandwidth on peers, media content is efficiently distributed to achieve the required streaming rate, as well as the streaming costs are minimized. In this paper, we seek to design simple, effective, and decentralized strategies to resolve conflicts among coexisting streaming overlays in their bandwidth competition and combine such strategies with network-coding-based media distribution to achieve efficient multioverlay streaming. Since such strategies of conflict are game theoretic in nature, we characterize them as a decentralized collection of dynamic auction games, in which downstream peers bid for upload bandwidth at the upstream peers for the delivery of coded media blocks. With extensive theoretical analysis and performance evaluation, we show that these local games converge to an optimal topology for each overlay in realistic asynchronous environments. Together with network-coding-based media dissemination, these streaming overlays adapt to peer dynamics, fairly share peer upload bandwidth to achieve satisfactory streaming rates, and can be prioritized.     

A performance evaluation of scalable live video streaming with nano data centers

To improve the efficiency and the quality of a service, a network operator may consider deploying a peer-to-peer architecture among controlled peers, also called here nano data centers, which contrast with the churn and resource heterogeneity of peers in uncontrolled environments. In this paper, we consider a prevalent peer-to-peer application: live video streaming. We demonstrate how nano data centers can take advantage of the self-scaling property of a peer-to-peer architecture, while significantly improving the quality of a live video streaming service, allowing smaller delays and fast channel switching. We introduce the branching architecture for nano datacenters (BAND), where a user can “pull” content from a channel of interest, or content could be “pushed” to it for relaying to other interested users. We prove that there exists an optimal trade-off point between minimizing the number of push, or the number of relaying nodes, and maintaining a robust topology as the number of channels and users get large, which allows scalability. We analyze the performance of content dissemination as users switch between channels, creating migration of nodes in the tree, while flow control insures continuity of data transmission. We prove that this p2p architecture guarantees a throughput independently of the size of the group. Analysis and evaluation of the model demonstrate that pushing content to a small number of relay nodes can have significant performance gains in throughput, start-up time, playback lags and channel switching delays.     

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.     

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。     

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.     

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。     

Robust control in cloud assisted peer to peer live streaming systems

Existing live video streaming systems can be classified as server (cloud) based or as peer-to-peer (P2P). The client–server approach promises stability and (Quality of Service) QoS by incurring expensive bandwidth provision cost on the server. On the other hand, P2P architecture is scalable with low bandwidth and maintenance cost. Here we propose a cloud assisted P2P live streaming architecture which is scalable and stable. In order to achieve this we have developed: (i) a scalable gossip protocol that monitors dynamically the total available bandwidth resources of the participating peers, (ii) a control strategy that dynamically allocates the bandwidth that is required.The first step towards this direction is to create a theoretical model that captures the dynamic relationship between the total bandwidth surplus/deficit and peers’ bandwidth utilization in order to be able to apply a control theoretical approach. Moreover, we quantify the impact of monitoring inaccuracies and peers’ dynamic bandwidth changes and we calculate analytically, as a function of them, the minimum amount of bandwidth overprovision that ensures the undisturbed distribution of the stream. System is evaluated through a detailed simulator of a complete P2P live streaming system and testified the uninterrupted and complete stream delivery even in very adverse bandwidth changes.     

基于P2P的流媒体点播系统中客户端缓存的研究

在Internet上提供大规模的VoD服务是一项具有挑战性的工作.首先提出一种基于P2P(peer to peer)方法的VoD服务体系PP_VoD,该系统通过在每个节点中开辟一段缓存空间来保存其最近所接收到的数据,以便为后续到达的节点提供服务,最后对该系统中客户端的缓存空间进行了详细的讨论.     

基于多路径的最优数据分配算法*

在对等网上利用多路径分发视频是一种重要的机制,虽然在一对节点之间找出符合条件的多条路径并不困难,但发送端如何从可用路径集中选出一个最优路径子集,并为其最优地分配发送速率和数据仍是一个难题。为此提出一种基于多路径的最优数据分配算法(optimal data allocation algorithm based on multiple path, ODAABMP)。首先应用数学规划理论建立最优数据分配模型,然后基于模型给出ODAABMP,并对ODAABMP输出解的最优性给出证明,最后通过实验验证了算法的有效性。     

结合CDN与P2P技术的混合流媒体系统研究

对基于CDN和P2P的流媒体系统进行了分析对比,指出了它们各自的优缺点,并根据因特网的结构特点,给出了一种结合这两种技术的混合流媒体系统的设计方案,提出了客户机端的内容缓存替换问题并给出了一种替换算法,对客户机离线的随机性与频繁性问题,文中给出了一种新的失效服务节点的快速替换查找策略。     

一种基于P2P的短视频分享系统

现有在线短视频分享策略通常采用C/S架构,给视频服务器带来较大的带宽压力。为此,提出一种采用点对点方式的在线短视频分享系统IShare,该系统结合用户点播偏好和视频文件之间的社会网络特性实现视频分享。IShare主要包括基于点播兴趣的节点分簇和视频数据源节点的查找2个核心技术。实验结果表明,IShare具备较好的视频数据源节点查找能力,可降低视频服务器带宽资源消耗。     

基于P2P视频点播技术的流媒体平台设计与开发

随着流媒体应用在Internet上的流行,传统C/S模式的流媒体服务系统已经不能满足流媒体对服务器性能和高带宽的要求,严重阻碍了流媒体业务质量的提高和容量的扩大。本文介绍一种基于P2P网络的流媒体播放技术,它将P2P网络技术和流媒体技术结合起来,充分利用客户计算机的资源,减轻流媒体服务器和网络负载,突破了传统的流媒体播放系统带宽瓶颈,能够保持播放节目流完整而流畅。本文还采用MVC模式和Java语言以面向对象方法设计和开发P2P流媒体网站,利用P2P流媒体技术,实现校园流媒体的视频点播。     

Measurement and enhancement of BitTorrent-based video file swarming

BitTorrent, the most popular P2P file sharing application over the Internet, has also been widely used for video file distribution, albeit in a download-and-play mode. In this paper, we extensively examine the characteristics of BT swarms with different contents through a large-scale measurement. Our study especially focuses on the existing video file swarms, trying to understand the potentials and challenges of providing streaming service in BitTorrent. Our results from intra-swarm, inter-swarm and AS-level measurements demonstrate that the video file swarms in the BitTorrent system are quite different from the non-video swarms. In particular, the preference bias terminates the long-term relationship between peers and raises a significant challenge to develop BT based streaming service. Fortunately, we find that most peer sets in video file swarms are good enough to support streaming service. Strong relationship between video file swarms is also observed from the inter-swarm measurement. This inter-swarm relationship can provide extra peer information for video file swarms. Therefore, the organization of existing peer information could be the key to mitigate the preference bias. To this end, a hypercomplex based virtual channel mechanism is proposed. We find that, quaternions can provide efficient and meaningful approximation in the bitfield operations. Using quaternion based three space rotation, our approach can help peers to avoid preference bias during the data delivery. This is especially helpful at the beginning of the downloading since the peer only has few local pieces. More importantly, this mechanism is transparent and friendly to the existing BT swarms with both video and non-video contents.     

结合IP组播的P2P流媒体直播系统

在流媒体系统中利用P2P技术与IP组播各自的优势,提出了一种结合IP组播的P2P流媒体直播系统,不仅能够充分利用用户节点的资源,减轻流媒体服务器与骨干网的负载,提高系统的可扩展性和可用性,而且有效地提高了P2P流媒体直播系统中视频流的服务质量。     

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.     

Resource-aware and quality-fair video-streaming using multiple adaptive TCP connections

In this paper, we present a resource-aware and quality-fair video content sharing system. When a video sharing server has insufficient uplink bandwidth and needs to serve multiple video content sharing services via streaming or downloading to other client peers using TCP transport, each service shares the limited uplink bandwidth equitably, due to the fair sharing characteristics inherent in TCP. However this bandwidth fair sharing cannot always guarantee quality fairness among the services, due to the specific requirements for video-streaming services, such as the playout rate and the size of the playout buffer. In our system, the server uses multiple TCP connections adaptively, depending on the anticipated status of each client playout buffer, to guarantee the bandwidth of each video-streaming session. By guaranteeing the quality of each video-streaming session, without the quality loss of other service sessions, the proposed system can successfully achieve service quality fairness. Simulation results show that our proposed algorithm can dramatically enhance the quality of each streaming session and thus provide service quality fairness among simultaneous multiple heterogeneous video-streaming services and content download services.