CollectCast: A peer-to-peer service for media streaming

We present CollectCast, a peer-to-peer (P2P) service for media streaming where a receiver peer is served by multiple sender peers. CollectCast operates at the application level but infers underlying network properties to correlate end-to-end connections between peers. The salient features of CollectCast include: (1) a novel multisender selection method that exploits the performance correlation and dependency among connections between different candidate senders and the receiver, (2) a customization of network tomography techniques and demonstration of improved practicality and efficiency, and (3) an aggregation-based P2P streaming mechanism that sustains receiver-side quality in the presence of sender/network dynamics and degradation. We have performed both real-world (on PlanetLab) and simulation evaluation of CollectCast. Our simulation results show that for a receiver, CollectCast makes better selection of multiple senders than other methods that do not infer underlying network properties. Our PlanetLab experiments are performed using a P2P media streaming application (called PROMISE) which we developed on top of CollectCast. Both packet-level and frame-level performance of MPEG-4 video streaming demonstrates the practicality and effectiveness of CollectCast.     

P2P流媒体中的数据分配算法

最近兴起的P2P技术在充分利用客户资源、提高系统的可伸缩性方面具有巨大的潜力,基于P2P提供视频服务已成为Internet的一项重要应用.在多对单P2P模式下,对多个发送端最优地分配发送速率和数据是一个难题.为此,提出了一种新的分配算法.首先,应用排队论把最优速率分配问题模型化为非线性最优化问题,推导出求解最优化问题的速率分配公式;然后,基于该公式提出最优速率分配算法(ORAA),并对ORAA输出解的最优性给出证明;最后,提出动态速率分配算法(DRAA).DRAA对动态的网络环境具有自适应性,能根据网络条件的变化最优地为多个发送端进行速率和数据分配.仿真实验结果表明,在不同的参数条件下,DRAA算法减少了计算和通信开销,比同类算法有更好的性能.     

Multiple sender distributed video streaming

With the explosive growth of video applications over the Internet, many approaches have been proposed to stream video effectively over packet switched, best-effort networks. We propose a receiver-driven protocol for simultaneous video streaming from multiple senders to a single receiver in order to achieve higher throughput, and to increase tolerance to packet loss and delay due to network congestion. Our receiver-driven protocol employs a novel rate allocation algorithm (RAA) and a packet partition algorithm (PPA). The RAA, run at the receiver, determines the sending rate for each sender by taking into account available network bandwidth, channel characteristics, and a prespecified, fixed level of forward error correction, in such a way as to minimize the probability of packet loss. The PPA, run at the senders based on a set of parameters estimated by the receiver, ensures that every packet is sent by one and only one sender, and at the same time, minimizes the startup delay. Using both simulations and Internet experiments, we demonstrate the effectiveness of our protocol in reducing packet loss.     

Adaptive receiver-driven streaming from multiple senders

This paper presents the design and evaluation of an adaptive streaming mechanism from multiple senders to a single receiver in Peer-to-Peer (P2P) networks, called P2P Adaptive Layered Streaming, or PALS. PALS is a receiver-driven mechanism. It enables a receiver peer to orchestrate quality adaptive streaming of a single, layer-encoded video stream from multiple congestion-controlled senders, and is able to support a spectrum of noninteractive streaming applications. The primary challenge in the design of a streaming mechanism from multiple senders is that available bandwidth from individual peers is not known a priori, and could significantly change during delivery. In PALS, the receiver periodically performs quality adaptation based on the aggregate bandwidth from all senders to determine: (i) the overall quality (i.e number of layers) that can be collectively delivered by all senders, and more importantly (ii) the specific subset of packets that should be delivered by individual senders in order to gracefully cope with any sudden change in their bandwidth. Our detailed simulation-based evaluations illustrate that PALS can effectively cope with several angles of dynamics in the system including: bandwidth variations, peer participation, and partially available content at different peers. We also demonstrate the importance of coordination among senders and examine key design tradeoffs for the PALS mechanism. Nazanin Magharei is currently a PhD student in the Computer Science Department at the University of Oregon. She received her BSc degree in Electrical Engineering from Sharif University of Technology, Iran in 2002. Her research interests include Peer-to-Peer streaming and multimedia caching. Reza Rejaie is currently an Assistant Professor at the Department of Computer and Information Science at the University of Oregon. From October 1999 to March 2002, he was a Senior Technical Staff member at AT&T Labs-Research in Menlo Park, California. He received a NSF CAREER Award for his work on P2P streaming in 2005. Reza has served on the editorial board of IEEE Communications Surveys & Tutorials, as well as the program committee of major networking conferences including INFOCOM, ICNP, Global Internet, ACM Multimedia, IEEE Multimedia, NOSSDAV, ICDCS, and MMCN. Reza received his MS and PhD degrees in Computer Science from the University of Southern California (USC) in 1996 and 1999, and his BS degree in Electrical Engineering from the Sharif University of Technology (Tehran, Iran) in 1991, respectively. Reza has been a member of both the ACM and IEEE since 1997.     

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.     

Multi-path continuous media streaming: what are the benefits?

Quality of service (QoS) in delivery of continuous media (CM) over the Internet is still relatively poor and inconsistent. Although many such applications can tolerate some degree of missing information, significant losses degrade an application’s QoS. In this paper, we investigate the potential benefits of mitigating this problem through the exploitation of multiple paths existing in the network between a set of senders and a receiver of CM. Our focus in this work is on providing a fundamental understanding of the benefits of using multiple paths to deliver CM over best-effort wide-area networks. Specifically, we consider pre-recorded CM applications and use the following metrics in evaluating the performance of multi-path streaming as compared to single-path streaming: (a) data loss rate, (b) conditional error burst length distribution, and (c) lag1-autocorrelation. The results of this work can be used in guiding the design of multi-path CM systems streaming data over best-effort wide-area networks.     

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.     

Distributed Collaboration for Enhanced Sender-Driven Video Streaming

We propose a sender-driven system for adaptive streaming from multiple servers to a single receiver over separate network paths. The servers employ information in receiver feedbacks to estimate the available bandwidth on the paths and then compute appropriate transmission schedules for streaming media packets to the receiver based on the bandwidth estimates. An optimization framework is proposed that enables the senders to compute their transmission schedules in a distributed way, and yet to dynamically coordinate them over time such that the resulting video quality at the receiver is maximized. To reduce the computational complexity of the optimization framework an alternative technique based on packet classification is proposed. The substantial reduction in online complexity due to the resulting packet partitioning makes the technique suitable for practical implementations of adaptive and efficient distributed streaming systems. Simulations with Internet network traces demonstrate that the proposed solution adapts effectively to bandwidth variations and packet loss. They show that the proposed streaming framework provides superior performance over a conventional distortion-agnostic scheme that performs proportional packet scheduling on the network paths according to their respective bandwidth values.     

Semantic scalability using tennis videos as examples

With advances in broadcasting technologies, people are now able to watch videos on devices such as televisions, computers, and mobile phones. Scalable video provides video bitstreams of different size under different transmission bandwidths. In this paper, a semantic scalability scheme with four levels is proposed, and tennis videos are used as examples in experiments to test the scheme. Rather than detecting shot categories to determine suitable scaling options for Scalable Video Coding (SVC) as in previous studies, the proposed method analyzes a video, transmits video content according to semantic priority, and reintegrates the extracted contents in the receiver. The purpose of the lower bitstream size in the proposed method is to discard video content of low semantic importance instead of decreasing the video quality to reduce the video bitstream. The experimental results show that visual quality is still maintained in our method despite reducing the bitstream size. Further, in a user study, we show that evaluators identify the visual quality as more acceptable and the video information as clearer than those of SVC. Finally, we suggest that the proposed scalability scheme in the semantic domain, which provides a new dimension for scaling videos, can be extended to various video categories.     

基于缓冲技术的网络带宽自适应码流控制策略

码流控制是网络多媒体服务中需要解决的主要问题之一.该文依据码流控制的主要影响因素--网络带宽,提出了一种基于网络带宽自适应的缓冲技术方案,先在接收端实时探测网络带宽反馈给网络服务发送端,按照网络带宽选择编码不同的数据分层,并进行了缓冲处理,然后输出传送码流,使得网络服务在适应网络不同带宽需求上具有灵活性.实验表明,使用该文带宽自适应缓冲技术方案,提高了预编码的MPEG视频流的传输质量.     

Joint remote control of an arbitrary single-qubit state by using a multiparticle entangled state as the quantum channel

We present a scheme for joint remote implementation of an arbitrary single-qubit operation following some ideas in one-way quantum computation. All the senders share the information of implemented quantum operation and perform corresponding single-qubit measurements according to their information of implemented operation. An arbitrary single-qubit operation can be implemented upon the remote receiver’s quantum system if the receiver cooperates with all the senders. Moreover, we study the protocol of multiparty joint remote implementation of an arbitrary single-qubit operation with many senders by using a multiparticle entangled state as the quantum channel.     

流媒体在Ad Hoc 网络中的多路径传输

提出了Ad Hoc 网络上多路径传输流媒体的框架，在Ad Hoc 网络中多路径同时传输流媒体以提高吞吐量并减小传输延迟。在发送端，采用部分解压缩算法对图像进行自适应分割，并通过多径源路由(MSR)协议根据负载均衡算法选择多条路由传输被拆分的数据；在接收端对数据进行缓存、图像重建恢复、JPEG解压缩及实时显示。实验表明，流媒体多路径传输实现了较好的图像传输质量和实时性。     

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.     

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.     

Network-adaptive autonomic transcoding algorithm for seamless streaming media service of mobile clients

As a result of improvements in wireless communication technologies, a multimedia data streaming service can now be provided for mobile clients. Since mobile devices have low computing power and work on a low network bandwidth, a transcoding technology is needed to adapt the original streaming media for mobile environments. However, wireless networks have variable bandwidths depending on the movement of clients and the communication distance from Access Point (AP). These characteristics make it hard to support stable Quality of Service (QoS) streams for mobile clients. In this paper, a target transcoding bit-rate decision algorithm is proposed to provide stable QoS streams for mobile clients. In our experiments, the proposed algorithm provides seamless streaming media services based on the network adaptive bit rate control and reduces transmission failure.     

Density-driven generalized regression neural networks (DD-GRNN) for function approximation.

This paper proposes a new nonparametric regression method, based on the combination of generalized regression neural networks (GRNNs), density-dependent multiple kernel bandwidths, and regularization. The presented model is generic and substitutes the very large number of bandwidths with a much smaller number of trainable weights that control the regression model. It depends on sets of extracted data density features which reflect the density properties and distribution irregularities of the training data sets. We provide an efficient initialization scheme and a second-order algorithm to train the model, as well as an overfitting control mechanism based on Bayesian regularization. Numerical results show that the proposed network manages to reduce significantly the computational demands of having individual bandwidths, while at the same time, provides competitive function approximation accuracy in relation to existing methods.     

对等网络副本最佳占有率缓存管理策略

随着对等网络应用的不断深入,如何减少时间延迟,减轻集中性带宽负载,提高服务质量,已经成为研究的一个重点.提出了CORPC缓存管理方案.该方案通过使用流媒体片段的流行度来定义媒体片段副本数可占用的最佳系统缓存容量,综合考虑流媒体片段已有的副本容量、流媒体片段的热度、系统节点存储容量,使用启发式贪婪算法来实现缓存准入和缓存替换机制.该方案兼顾了不同热度的媒体片段的服务质量.模拟环境的测试结果表明,随着节点缓存空间的增加,系统服务质量得到改善.     

Extending RSVP for quality of security service

The resource reservation protocol (RSVP) lets hosts request quality of (bandwidth) service for multicast applications on the Internet. As network equipment advances to provide improved bandwidth service, security service becomes the more critical problem. However, RSVP doesn't provide a flexible mechanism to support quality of security service (QoSS). Security service RSVP extends RSVP to provide the needed mechanism for dynamically negotiating QoSS among the senders and receivers of multicast applications on the Internet. SSRSVP provides different QoSS resolutions according to receiver nodes' security service needs.