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。     

基于改进粒子群算法的P2P流媒体数据调度策略

根据P2P流媒体数据调度特点,改进了粒子群优化算法,并提出适用于离散粒子群算法（MDPSOA）的数字串编码方式。调度策略引入资源紧急度以及资源稀缺度来选择调度数据片,然后用改进离散粒子群算法来进行节点寻优,找出最优调度节点集。最后通过实验仿真算法收敛性、数据调度时间、网络利用带宽和节点负载平衡,从而验证调度策略的可行性和有效性。     

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。     

An efficient playout smoothing mechanism for layered streaming in P2P networks

Layered video streaming in peer-to-peer (P2P) networks has drawn great interest, since it can not only accommodate large numbers of users, but also handle peer heterogeneity. However, there’s still a lack of comprehensive studies on chunk scheduling for the smooth playout of layered streams in P2P networks. In these situations, a playout smoothing mechanism can be used to ensure the uniform delivery of the layered stream. This can be achieved by reducing the quality changes that the stream undergoes when adapting to changing network conditions. This paper complements previous efforts in throughput maximization and delay minimization for P2P streaming by considering the consequences of playout smoothing on the scheduling mechanisms for stream layer acquisition. The two main problems to be considered when designing a playout smoothing mechanism for P2P streaming are the fluctuation in available bandwidth between peers and the unreliability of user-contributed resources—particularly peer churn. Since the consideration of these two factors in the selection and scheduling of stream layers is crucial to maintain smooth stream playout, the main objective of our smoothing mechanism becomes the determination of how many layers to request from which peers, and in which order. In this work, we propose a playout smoothing mechanism for layered P2P streaming. The proposed mechanism relies on a novel scheduling algorithm that enables each peer to select appropriate stream layers, along with appropriate peers to provide them. In addition to playout smoothing, the presented mechanism also makes efficient use of network resources and provides high system throughput. An evaluation of the performance of the mechanism demonstrates that the proposed mechanism provides a significant improvement in the received video quality in terms of lowering the number of layer changes and useless chunks while improving bandwidth utilization.     

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.     

基于网络编码的对等网流媒体传输模型和算法

在对等网(peer-to-peer,简称P2P)流媒体系统中,节点(用户)的输出带宽(上行带宽)容量利用率的提高能够降低服务器的带宽开销.网络编码可以实现组播的最大吞吐率,因而具有提高系统中节点输出带宽容量利用率的潜力.将随机线性网络编码应用到P2P流媒体系统中,建立了基于随机线性网络编码的P2P流媒体传输过程模型,并据此建立传输算法的优化模型,比较研究了贪婪式算法、最少者优先算法和随机算法等.优化结果表明,随机算法可以平等均匀地获取数据包,能够最充分地利用节点的输出带宽容量,降低服务提供商的运营成本.通过对优化模型解的分析对实际系统中的传输算法给出了设计指导原则.     

An efficient server bandwidth costs decreased mechanism towards mobile devices in cloud-assisted P2P-VoD system

Recently, more and more devices with small buffer size such as PDAs or mobile phones are joining in the VoD system, which leads to two major challenges: how to efficiently distribute their bandwidth resources with small buffer size, and how to provide assistant mechanism to make them playback smoothness. In face of this situation and for the purpose of decreasing the server bandwidth costs, we propose a peers’ downloading mechanism called NCDLT to solve above challenges. It contains two algorithms. The first is neighbors and chunks downloading selection (NCS) algorithm and it ensures peers to find neighbors who can provide video data with lower refusal rate. The second is distributed linear taxation algorithm (DLT) and it makes peers with lower capability acquire enough download rate to reduce the request to servers. The simulation results demonstrate that our algorithms can offload the server bandwidth costs and improve the download rate of peers with small buffer size.     

Characterizing peers communities and dynamics in a P2P live streaming system

Despite the large number of works devoted to understand P2P live streaming applications, most of them put forth so far rely on characterizing the static view of these systems. In this work, we characterize the SopCast, one of the most important P2P live streaming applications. We focus on its dynamics behavior as well as on the community formation phenomena. Our results show that SopCast presents a low overlay topology diameter and low end-to-end shortest path. In fact, diameter is smaller than 6 hops in almost 90 % of the observation time. More than 96 % of peers’ end-to-end connections present only 3 hops. These values combined may lead to low latencies and a fast streaming diffusion. Second, we show that communities in SopCast are well defined by the streaming data exchange process. Moreover, the SopCast protocol does not group peers according to their Autonomous System. In fact, the probability that a community contains 50 % of its members belonging to the same AS (when we observe the largest AS of our experiments) is lower then 10 %. Peers exchange more data with partners belonging to the same community instead of peers inside the same AS. For the largest AS we have, less than 18 % of peer traffic has been exchanged with another AS partners. Finally, our analysis provides important information to support the future design of more efficient P2P live streaming systems and new protocols that exploit communities’ relationships.     

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.     

Adaptive content-and-deadline aware chunk scheduling in mesh-based P2P video streaming

In mesh-based Peer-to-Peer (P2P) live video streaming systems packet scheduling is an important factor in overall video playback quality. In mesh based P2P video streaming systems, each video sequence is divided into chunks, which are then distributed by multiple suppliers to the receivers. The suppliers need to be coordinated by the receiver through specifying a transmission schedule for each of them. Many previous studies on scheduling of P2P streaming tend to mainly focus on networking issues which strongly depend on a particular P2P architecture such as tree or mesh. These algorithms suffer from some design issues: 1) they are too complex to deploy, 2) they do not take video characteristics into account and 3) they do not have sender-side transmission policy. To address all three of these problems, we propose a new chunk scheduling scheme which consists of two parts: i) receiver-side scheduler and ii) sender-side transmission order scheme. The proposed receiver-side scheduler considers the contribution level of each video frame as well as the frame’s urgency in order to define a priority for each video frame. It attempts to request frames with highest priority from peers which can deliver them in a shorter time. We also design a new chunk transmission order scheme that decides which requested chunk will be sent out first based on its importance to the requesting neighbor. Our simulation results show that the proposed scheduling scheme improves the overall quality of the perceived video in mesh-based P2P video streaming architectures substantially.     

Fast-Mesh: A Low-Delay High-Bandwidth Mesh for Peer-to-Peer Live Streaming

Peer-to-peer (P2P) technology has emerged as a promising scalable solution for live streaming to a large group. In this paper, we address the design of an overlay mesh which achieves low source-to-peer delay, accommodates asymmetric and diverse uplink bandwidth, and continuously improves delay based on an existing pool of peers. By considering a streaming mesh as an aggregation of data flows along multiple spanning trees, the peer delay in the mesh is then its longest delay (including both propagation and scheduling delay) among all the trees. Clearly, such delay can be very high if the mesh is not designed well. In this paper, we propose and study a mesh protocol called Fast-Mesh, which optimizes such delay while meeting a certain streaming bandwidth requirement. Fast-Mesh is particularly suitable for a mildly dynamic network consisting of proxies, supernodes, or content distribution servers.      

P2P视频直播数据调度算法

P2P技术解决了传统流媒体应用中的不能支持大用户的问题.而数据调度算法一直是P2P研究中的热点问题.在给出了P2P视频直播系统中节点能力的定义和计算方法后,结合BT中的Rarest First策略,提出了一种基于节点能力的适用于P2P视频直播系统的数据调度算法.该算法既考虑了流媒体数据具有时间限制的特性,同时也考虑了如何能充分的利用节点的上传带宽,增进了系统的负载平衡.     

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.     

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.     

基于综合因素的P2P流媒体数据调度算法

为了提高P2P流媒体数据传输的效率,提出一种基于综合因素的P2P流媒体数据调度算法,该算法综合考虑数据块的提供者数量和紧急程度定义数据块优先级,并对与提供者之间的网络带宽进行有效估计,根据优先级和带宽调度P2P数据请求的次序和方向。仿真结果表明,该调度算法在节点吞吐量和系统连续性指标以及启动延迟方面比传统的P2P流媒体调度算法有明显提高。     

SimplyRep: A simple and effective reputation system to fight pollution in P2P live streaming

Peer-to-Peer (P2P) streaming has become a popular platform for transmitting live content. However, due to their increasing popularity, P2P live streaming systems may be the target of user opportunistic actions and malicious attacks, which may greatly reduce streaming rate or even stop it completely. In this article, we focus on a specific type of attack called content pollution, in which malicious peers tamper or forge media data, introducing fake content before uploading it to their partners in the overlay network. Specifically, we present a new decentralized reputation system, named SimplyRep, that quickly identifies and penalizes content polluters, while incurring in low overhead in terms of bandwidth consumption. We evaluate our method with both simulation and experiments in PlanetLab, comparing it against two previously proposed approaches, namely, a centralized black list and a distributed reputation system, in various scenarios. Our results indicate that SimplyRep greatly outperforms the two alternatives considered. In particular, both black list and the distributed reputation method perform poorly when polluters act jointly in a collusion attack, reaching a data retransmission overhead (triggered by polluted chunks received) of 70% and 30%, respectively, whereas the overhead experienced by SimplyRep is at most 2%. Our results also show that SimplyRep is able to quickly isolate almost all polluters under a dissimulation attack, being also somewhat robust to a whitewashing attack, although the latter remains a challenge to effective P2P streaming.     

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.     

基于P2P的流媒体直播技术研究与展望

覆盖网络的组织与维护对于P2P流媒体直播系统的性能有着极其重要的影响.根据覆盖网络拓扑组织形式的不同,分别研究了基于单树结构、多树结构、随机拓扑结构的现有P2P流媒体直播技术方案,并结合节点的动态行为和传输延迟对方案的优缺点进行了分析比较.以此为基础概括总结有待解决的主要问题,展望了未来的研究方向,为基于P2P流媒体直播的进一步的研究和应用提供有益的参考.     

一种基于P2P点组技术的流媒体协作计算

分析了流媒体技术的现状和问题，讨论了在P2P环境下的流媒体多点分布式调度技术和调度性能分析，以及多点调度下的带宽分配算法，最后给出了一个基于P2P点组的流媒体协作调度模型。