EUE principle of resource scheduling for live streaming systems underlying CDN-P2P hybrid architecture

Peer-to-peer live streaming offers plenty of live television programs for users, and has become one of the most popular Internet applications. However, some ubiquitous problems such as long startup delay and unsmooth playback seriously restrict the quality of service of live streaming, whereas deploying dedicated servers immoderately will suffer from excessive costs. In this paper, we introduce economical-underloaded-emergent (EUE) principle to instruct resource scheduling for live streaming systems based on CDN-P2P hybrid architecture. Complying with this principle, we differentiate peers?? chunk requests according to their playback deadline and propose a set of mechanisms to provide distinct service for diverse requests. The results of simulation experiment demonstrate that EUE principle effectively optimize system performance, and achieve the remarkable reduction of startup delay and increase of chunk arrival ratio.     

一种面向线性相关冗余优化的源节点选择算法

基于网络编码的P2P流媒体直播系统的优势之一在于多个源节点之间不需要显式的协同调度也能有效地服务于请求节点。但正是由于缺乏协同,即使编码系数的有限域足够大,仍然存在线性相关冗余数据,从而浪费了源节点的带宽。分析了这一问题产生的原因,并提出采用从tracker提供的源节点集合中选择部分节点作为活动源节点来解决该问题。活动源节点最优选择问题可以归约为0-1背包问题的变种,是NP难的,因此我们设计了一个多项式时间的近似算法来逼近最优解。通过形式化证明和模拟,我们验证了该算法的可行性。数据表明该方法能够进一步提高P2P流媒体直播系统的服务质量。     

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。     

基于图着色的P2P流媒体数据调度算法

为了提高P2P流媒体的传输性能,提出一种基于图着色的数据调度算法。算法规定加入系统的每个节点和数据块都被分配某种颜色,请求节点优先获取相同颜色的数据块。根据数据稀有性、紧急性、新鲜性定义数据块优先级别,同时评估伙伴节点数据提供能力,以选择恰当的数据提供者。该算法能有效平衡节点负载,合理利用系统带宽,使数据分布更均匀,提高了系统传输性能。仿真实验表明,算法在数据填充率、启动延迟、数据到达率等重要指标上都优于传统数据调度算法。     

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.     

基于能力因子的P2P邻居节点随机可变选择算法

在分析固定随机选择邻居节点算法的基础上,提出了一种适用于混合式P2P直播系统的邻居节点随机可变选择算法,新算法通过能力因子来衡量节点的良好度,对不同类的节点有不同的邻居数量的最大值,使得良好度高的节点能发挥更大的作用,仿真表明算法能降低数据传输的延迟,提高网络系统的性能。     

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 modeling framework of content pollution in Peer-to-Peer video streaming systems

Peer-to-Peer (P2P) live video streaming systems are known to suffer from intermediate attacks due to its inherent vulnerabilities. The content pollution is one of the common attacks that have received little attention in P2P live streaming systems. In this paper, we propose a modeling framework of content pollution in P2P live streaming systems. This model considers both unstructured and structured overlays, and captures the key factors including churns, user interactions, multiple attackers and defensive techniques. The models are verified with simulations and implemented in a real working system, Anysee. We analyze content pollution and its effect in live streaming system. We show that: (1) the impact from content pollution can exponentially increase, similar to the random scanning worms, leading to playback interruption and unnecessary bandwidth consumption; (2) content pollution is influenced by peer cooperation, peer degree and bandwidth in unstructured overlays, and topology breadth in structured ones; (3) the structured overlay is more resilient to content pollution; (4) a hybrid overlay result in better reliability and pollution resistance; (5) hash-based chunk signature scheme is most promising against content pollution.     

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.     

P2P流媒体直播分布式缓存替换算法研究

P2P流媒体直播系统中分布式节点缓存区别于传统的Client/Server缓存结构,节点的实时同步给缓存管理提出较大挑战。分析了分布式缓存空间利用率的决定因素,通过节点成功请求比率,缓存的fresh度及数据分片点击率3个指标来评估节点缓存空间利用率,提出了频度限制与改进的LRU相结合的K-Degree&LRU2缓存替换算法。仿真实验结果表明,该算法较传统的FIFO、LRU算法具有更高的执行效率。     

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.     

SecP2PVoD: a secure peer-to-peer video-on-demand system against pollution attack and untrusted service provider

The Peer-to-Peer video-on-demand (P2P-VoD) streaming has become widespread in recent years. Unlike the traditional client-server model based video-streaming, the P2P-VoD leverages the peer’s capacity of upload bandwidth for the delivery of video contents in a distributed network. The P2P environment is susceptible to various security threats, in which the pollution attack is one of the potentially destructive threats. Moreover, video streaming is prone to other security challenges, such as authenticity, confidentiality, authorization, and integrity. There have been discussed four possible protection to the pollution attack: blacklisting, hash verification, traffic encryption, and chunk signing. In this paper, we present escrow-free identity-based signcryption (EF-IDSC) scheme for secure data transmission scheme in P2P-VoD streaming with an untrusted service provider. The proposed system enables a peer to establish a session key with other peer using the asymmetric key algorithm. The security analysis shows that the proposed P2P-VoS system prevents pollution attacks under well-known random oracle model and achieves privacy, confidentiality, and subscriber authentication simultaneously. The experimental evaluation shows that the proposed scheme has better computation and communication costs as compared to the related schemes.

     

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.     

Delay Management in Mesh-Based P2P Live Streaming Using a Three-Stage Peer Selection Strategy

Peer-to-peer (P2P) live streaming systems have gained popularity due to the self-scalability property of the P2P overlay networks. In P2P live streaming, peers retrieve stream content from other peers in the system. Therefore, peer selection strategy is a fundamental element to build an overlay which manages the playback delay and startup delay experienced by the peers. In this paper, we propose a peer selection strategy which manages to build a minimum delay overlay using three different stages of overlay construction. In the first stage, the tracker suggests some peers as prospective partners to a new peer. In the second stage, the peer selects its partners out of these peers such that delay is minimized. The third stage is the topology adaptation phase of peers, where peers reposition themselves in the overlay to maintain minimum delay during peer churn. In the proposed peer selection strategy, peers are selected in all the stages based on parameters such as propagation delay, upload capacity, buffering duration and buffering level. The proposed strategy is compared with two existing strategies in the literature: Fast-Mesh (Ren et al. in IEEE Trans Multimed 11: 1446, 2009) and Hybrid live p2p streaming protocol (Hammami et al., 2014) using simulations. Our results show that playback delay and startup delay are reduced significantly with the help of proposed strategy. We demonstrate that the stability of the system also improves during peer churn.     

Proxy caching for peer-to-peer live streaming

Peer-to-Peer (P2P) live streaming has become increasingly popular over the Internet. To alleviate the inter-ISP traffic load and to minimize the access latency, proxy caching has been widely suggested for P2P applications. In this paper, we carry out an extensive measurement study on the properties of P2P live streaming data requests. Our measurement demonstrates that the P2P living streaming traffic exhibits strong localities that could be explored by caching. This is particularly noticeable for the temporal locality, which is often much weaker in the conventional P2P file sharing applications. Our results further suggest that the request time of the same data piece from different peers exhibits a generalized extreme value distribution. We then propose a novel sliding window (SLW)-based caching algorithm, which predicts and caches popular data pieces according to the measured distribution. Our experimental results suggest that the P2P live streaming can greatly benefit from the proxy caching. And, with much lower overhead, our SLW algorithm works closer to an off-line optimal algorithm that holds the complete knowledge of future requests.     

On scalability of proximity-aware peer-to-peer streaming

P2P (peer-to-peer) technology has proved itself an efficient and cost-effective solution to support large-scale multimedia streaming. Different from traditional P2P applications, the quality of P2P streaming is strictly determined by performance metrics such as streaming delay. To meet these requirements, previous studies resorted to intuitions and heuristics to construct peer selection solutions incorporating topology and proximity concerns. However, the impact of proximity-aware methodology and delay tolerance of peers on the scalability of P2P system remains an unanswered question. In this paper, we study this problem via an analytical approach. To address the challenge of incorporating Internet topology into P2P streaming analysis, we construct a H-sphere network model which maps the network topology from the space of discrete graph to the continuous geometric domain, meanwhile capturing the power-law property of Internet. Based on this model, we analyze a series of peer selection methods by evaluating their performance via key scalability metrics. Our analytical observations are further verified via simulation on Internet topologies.     

Defending Against Buffer Map Cheating in DONet-Like P2P Streaming

Data-driven Overlay Network (DONet)-like P2P system is especially suitable to support live stream applications, since its data structure can tolerate node dynamics quite well. However, optimal streaming demands the cooperation of individual nodes. If selfish nodes cheat about their buffer maps to reduce the forwarding burden, the overall streaming quality would be negatively affected. To defend against this kind of cheating, we design a trustworthy service-differentiation based incentive mechanism with low complexity in this paper. The mechanism is composed of the service-differentiation algorithm and the contribution-evaluation algorithm. Compared with other studies in this area, the primary characteristic of our mechanism lies in two aspects. Firstly, the contribution of each node is evaluated considering the features of live streaming, not just by the transferring bytes. Secondly, the potential cheating behavior of overlay nodes during the fulfillment of incentive algorithms can be avoided, which is usually not considered by other similar studies. Extensive simulations suggest that the algorithms are indeed effective for defending against buffer map cheating in DONet-like P2P streaming.      

A Payment-Based Incentive and Service Differentiation Scheme for Peer-to-Peer Streaming Broadcast

We propose a novel payment-based incentive scheme for peer-to-peer (P2P) live media streaming. Using this approach, peers earn points by forwarding data to others. The data streaming is divided into fixed length periods; during each of these periods peers compete with each other for good parents (data suppliers) for the next period in a first-price-auction-like procedure using their points. We design a distributed algorithm to regulate peer competitions, and consider various individual strategies for parent selection from a game theoretic perspective. We then discuss possible strategies that can be used to maximize a peer's expected media quality by planning different bids for its substreams. Finally, in order to encourage off-session users to remain staying online and continue contributing to the network, we develop an optimal data forwarding strategy that allows peers to accumulate points that can be used in future services. Simulations results show that proposed methods effectively differentiate the media qualities received by peers making different contributions (which originate from, for example, different forwarding bandwidths or servicing times), and at the same time maintaining a high overall system performance.     

A suitable server placement for peer-to-peer live streaming

With the rapid growth of the scale, complexity, and heterogeneity of Peer-to-Peer (P2P) systems, it has become a great challenge to deal with the peer’s network-oblivious traffic and self-organization problems. A potential solution is to deploy servers in appropriate locations. However, due to the unique features and requirements of P2P systems, the traditional placement models cannot yield the desirable service performance. To fill this gap, we propose an efficient server placement model for P2P live streaming systems. Compared to the existing solutions, this model takes the Internet Service Provider (ISP) friendly problem into account and can reduce the cross-network traffic among ISPs. Specifically, we introduce the peers’ contribution into the proposed model, which makes it more suitable for P2P live streaming systems. Moreover, we deploy servers based on the theoretical solution subject to practical data and apply them to practical live streaming applications. The experimental results show that this new model can reduce the amount of cross-network traffic and improve the system efficiency, has a better adaptability to Internet environment, and is more suitable for P2P systems than the traditional placement models.     

Investigating the Scheduling Sensitivity of P2P Video Streaming: An Experimental Study

Peer-to-peer (P2P) technology has recently been employed to deliver large scale video multicast services on the Internet. Considerable efforts have been made by both academia and industry on P2P streaming design. While academia mostly focus on exploring design space to approach the theoretical performance bounds, our recent measurement study on several commercial P2P streaming systems indicates that they are able to deliver good user quality of experience with seemingly simple designs. One intriguing question remains: how elaborate should a good P2P video streaming design be? Towards answering this question, we developed and implemented several representative P2P streaming designs, ranging from theoretically proved optimal designs to straightforward “naive” designs. Through an extensive comparison study on PlanetLab, we unveil several key factors contributing to the successes of simple P2P streaming designs, including system resource index, server capacity and chunk scheduling rule, peer download buffering and peering degree. We also identify regions where naive designs are inadequate and more elaborate designs can improve things considerably. Our study not only brings us better understandings and more insights into the operation of existing systems, it also sheds lights on the design of future systems that can achieve a good balance between the performance and the complexity.