自适应的分段代理缓存传输策略

结合现有的代理缓存策略和传输方案,针对现有的网络条件,提出了一种自适应的分段方法,解决了已有方法对于流媒体对象流行性的变化和用户访问模式的不确定缺乏自身调整能力的缺欠,和一种优化的传输方案,采用了单播和多播相结合, 主动预取和补丁传输相结合的方法,对于缩短启动延时、提高字节命中率以及节省骨干网带宽等方面取得了较明显的效果.     

Optimal proxy cache allocation for efficient streaming media distribution

We address the problem of efficiently streaming a set of heterogeneous videos from a remote server through a proxy to multiple asynchronous clients so that they can experience playback with low startup delays. We determine the optimal proxy prefix cache allocation to the videos that minimizes the aggregate network bandwidth cost. We integrate proxy caching with traditional server-based reactive transmission schemes such as hatching, patching and stream merging to develop a set of proxy-assisted delivery schemes. We quantitatively explore the impact of the choice of transmission scheme, cache allocation policy, proxy cache size, and availability of unicast versus multicast capability, on the resulting transmission cost. Our evaluations show that even a relatively small prefix cache (10%-20% of the video repository) is sufficient to realize substantial savings in transmission cost. We find that carefully designed proxy-assisted reactive transmission schemes can produce significant cost savings even in a predominantly unicast environment such as the Internet.     

A proxy architecture for collaborative media streaming

Streaming media from the Internet is a successful application for end-users. With the upcoming success of mobile devices and home networking environments, cooperation among users will become more important in the future. To achieve such cooperation, explicit middleware standards have been defined. On the other hand, Internet conferencing applications do not handle collaborative streaming sessions with individual control for each user. We propose a new concept for cooperation exemplary for collaborative media streaming using IETF multimedia session control protocols together with a proxy architecture. This concept enables both synchronization among clients and flexible control to individual users.     

Segment-based streaming media proxy: modeling and optimization

Researchers often use segment-based proxy caching strategies to deliver streaming media by partially caching media objects. The existing strategies mainly consider increasing the byte hit ratio and/or reducing the client perceived startup latency (denoted by the metric delayed startup ratio). However, these efforts do not guarantee continuous media delivery because the to-be-viewed object segments may not be cached in the proxy when they are demanded. The potential consequence is playback jitter at the client side due to proxy delay in fetching the uncached segments, which we call proxy jitter. Thus, for the best interests of clients, a correct model for streaming proxy system design should aim to minimize proxy jitter subject to reducing the delayed startup ratio and increasing the byte hit ratio. However, we have observed two major pairs of conflicting interests inherent in this model: (1) one between improving the byte hit ratio and reducing proxy jitter, and (2) the other between improving the byte hit ratio and reducing the delayed startup ratio. In this study, we first propose and analyze prefetching methods for in-time prefetching of uncached segments, which provides insights into the first pair of conflicting interests. Second, to address the second pair of the conflicting interests, we build a general model to analyze the performance tradeoff between the second pair of conflicting performance objectives. Finally, considering our main objective of minimizing proxy jitter and optimizing the two tradeoffs, we propose a new streaming proxy system called Hyper Proxy. Synthetic and real workloads are used to evaluate our system. The performance results show that Hyper Proxy generates minimum proxy jitter with a low delayed startup ratio and a small decrease of byte hit ratio compared with existing schemes.     

基于云计算的多路网络流媒体分布式最优存储与分配策略

针对云计算系统在执行任务过程中的能量消耗过多、处理速度不理想等情况,提出一种基于云计算的多路网络流媒体分布式最优存储与分配策略.通过构建基于云计算的数学模型来分析执行任务时的能量消耗情况,采用基于虚拟调度机制的分布式最优存储策略来实现在满足存储需求的情况下减少服务器进行存储时的能量消耗总量,最小化存储成本,并采用基于动态决策规则的分配策略来根据服务器的功率、性能以及负载情况进行任务调度,使云计算系统在满足服务质量要求的条件下,充分利用系统运作能耗,不产生过多空闲能耗.实验及结果分析表明,所提出的分布式最优存储与分配策略在节省能量消耗、提升运行速度上发挥了较好的效果.     

Location service and session mobility for streaming media applications in home networks

In the near future, home networks are expected to become an important part of the user's ubiquitous environment. However, how to provide service discovery and multimedia services in such networks becomes a great challenge. In the paper, we propose an extension header, referred to as the “MediaService” header, into the Session Initiation Protocol to provide video streaming service. The streaming control and session mobility functions are also considered in the MediaService header. We also propose a peer to peer Service Location Protocol architecture for users to search for location of services across domains. We added a Substitute Request Message and cache policy into the Service Location Protocol to search for location of services across domains. A prototype implementation shows the performance of our prototype.     

Dynamic file grouping for load balancing in streaming media clustered server systems

A dynamic file grouping strategy is presented to address the load balancing problem in streaming media clustered server systems. This strategy increases the server cluster availability by balancing the workloads among the servers within a cluster. Additionally, it improves the access hit ratio of cached files in delivery servers to alleviate the limitation of I/O bandwidth of storage node. First, the load balancing problem is formulated as a two layers semi-Markov switching state-space control process. This analytic model captures the behaviors of streaming media clustered server systems accurately, and is with constructional flexibility and scalability. Then, a policy iteration based reinforcement learning algorithm is proposed to optimize the file grouping policy online. By utilizing the features of the event-driven policy, the proposed optimization algorithm is adaptive and with less computational cost. Simulation results demonstrate the effectiveness of the proposed approach. Recommended by Editor Hyun Seok Yang. This work was supported by the National Natural Science Foundation of China under grant Nos. 60774038, 60574065, National 863 HI-TECH Research & Development Plan of China under grant Nos. 2006AA01Z114, 2008AA01A317, Natural Science Foundation of Anhui Province under grant No. 070412063, Graduate Student Innovation Foundation of USTC under grant No. KD2006036, and Science Research Development Foundation of HFUT under grant No. GDBJ2008-045. Qi Jiang received the B.S. degree in Industrial Electrical Automation from Southeast University in 1989 and the Ph.D. degree in Control Science and Engineering from University of Science and Technology of China in 2008. He is currently a Post-doc in USTC. His research interests include optimization and control of stochastic dynamic systems, and performance analysis and optimization of network communication systems. Hong-Sheng Xi received the M.S. degree in Applied Mathematics from University of Science and Technology of China in 1977. He is currently a Professor in Department of Automation, USTC. His research interests include discrete event dynamic systems, performance analysis and optimization of network communication systems, robust control, and network security. Bao-Qun Yin received the B.S. degree in Mathematics from Sichuan University in 1985, the M.S. degree in Applied Mathematics and the Ph.D. degree in Pattern Recognition and Intelligent Systems from University of Science and Technology of China in 1993 and 1998, respectively. He is currently a Professor in Department of Automation, USTC. His research interests include discrete event dynamic systems, and Markov decision processes.     

Minimizing delivery cost in scalable streaming content distribution systems

Recent scalable multicast streaming protocols for on-demand delivery of media content offer the promise of greatly reduced server and network bandwidth. However, a key unresolved issue is how to design scalable content distribution systems that place replica servers closer to various client populations and route client requests and response streams so as to minimize the total server and network delivery cost. This issue is significantly more complex than the design of distribution systems for traditional Web files or unicast on-demand streaming, for two reasons. First, closest server and shortest path routing does not minimize network bandwidth usage; instead, the optimal routing of client requests and server multicasts is complex and interdependent. Second, the server bandwidth usage increases with the number of replicas. Nevertheless, this paper shows that the complex replica placement and routing optimization problem, in its essential form, can be expressed fairly simply, and can be solved for example client populations and realistic network topologies. The solutions show that the optimal scalable system can differ significantly from the optimal system for conventional delivery. Furthermore, simple canonical networks are analyzed to develop insights into effective heuristics for near-optimal placement and routing. The proposed new heuristics can be used for designing large and heterogeneous systems that are of practical interest. For a number of example networks, the best heuristics produce systems with total delivery cost that is within 16% of optimality.     

A sequential Kriging method assisted by trust region strategy for proxy cache size optimization of the streaming media video data due to fragment popularity distribution

Multimedia Tools and Applications - The Kriging method based on machine learning is an attractive tool. In this work, a sequential Kriging method assisted by trust region strategy (SKM-TRS) is...     

Double feedback streaming agent for real-time delivery of media over 3G wireless networks

A network agent located at the junction of wired and wireless networks can provide additional feedback information to streaming media servers to supplement feedbacks from clients. Specifically, it has been shown that feedbacks from the network agent have lower latency, and they can be used in conjunction with client feedbacks to effect proper congestion control. In this work, we propose the double-feedback streaming agent (DFSA) which further allows the detection of discrepancies in the transmission constraints of the wired and wireless networks. By working together with the streaming server and client, DFSA reduces overall packet losses by exploiting the excess capacity Of the path with more capacity. We show how DFSA can be used to support three modes of operation tailored for different delay requirements of streaming applications. Simulation results under high wireless latency show significant improvement of media quality using DFSA over non-agent-based and earlier agent-based streaming systems.     

Throughput optimization for video streaming proxy servers based on video staging

A video streaming proxy server needs to handle hundreds of simultaneous connections between media servers and clients. Inside, every video arrived at the server and delivered from it follows a specific arrival and delivery schedule. While arrival schedules compete for incoming network bandwidth, delivery schedules compete for outgoing network bandwidth. As a result, a proxy server has to provide sufficient buffer and disk cache for storage, together with memory space, disk space and disk bandwidth. In order to optimize the throughput, a proxy server has to govern the usage of these resources. In this paper, we first analyze the property of a traditional smoothing algorithm and a video staging algorithm. Then we develop, based on the smoothing algorithm, a video staging algorithm for video streaming proxy servers. This algorithm allows us to devise an arrival schedule based on the delivery schedule. Under this arrival and delivery schedule pair, we can achieve a better resource utilization rate gracefully between different parameter sets. It is also interesting to note that the usage of the resources such as network bandwidth, disk bandwidth and memory space becomes interchangeable. It provides the basis for inter-resource scheduling to further improve the throughput of a video streaming proxy server system.

CBC: Caching for cloud-based VOD systems

Cloud-based video on demand (VOD) service is a promising next-generation media streaming service paradigm. Being a resource-intensive application, how to maximize resource utilization is a key issue of designing such an application. Due to the special cloud-based VOD system architecture consisting of cloud storage cluster and media server cluster, existing techniques such as traditional caching strategies are inappropriate to be adopted by a cloud-based VOD system directly in practice. Therefore, in this study, we have proposed a systemic caching scheme, which seamlessly integrates a caching algorithm and a cache deployment algorithm together to maximize the resources utilization of cloud-based VOD system. Firstly, we have proposed a cloud-based caching algorithm. The algorithm models the cloud-based VOD system as a multi-constraint optimization problem, so as to balance the resource utilization between cloud storage cluster and media server cluster. Secondly, we have proposed a cache deployment algorithm. The algorithm further manages the bandwidth and cache space resource utilization inside the media server cluster in a more fine-grained manner, and achieves load balancing performance. Our evaluation results show that the proposed scheme enhances the resource utilization of the cloud-based VOD system under resource-constrained situation, and cuts down the reject ratio of user requests.     

Practical design of a proxy agent to facilitate adaptive video streaming service across wired/wireless networks

Thanks to the growing of the wireless networks, the video streaming application becomes a ubiquitous joyful service. In a wireless communication network environment, the service traffic spans across the wired and wireless domains. In this article, we propose a practical design of a proxy agent - SPONGE (Stream Pooler Over a Network Graded Environment) sitting between the wireless User Equipments (UEs) and the video streaming server to facilitate the adaptive video streaming service across wired/wireless networks. To make the wireless streaming service more efficient, an input video session would be encoded as multiple qualities of video streams so that UEs with a similar receiving condition can share streams with the same service quality via SPONGE. SPONGE can alleviate the direct load on the original stream broadcasting server. Meanwhile, it can make each UE get an adaptive streaming service according to the network conditions of the UE by a reduced network condition feedback latency. Our theoretical analysis and simulation results show that SPONGE can help wireless streaming users get a smooth and better playback quality by a quick and accurate reaction to the network condition.     

Network-aware partial caching for Internet streaming media

The delivery of multimedia over the Internet is affected by adverse network conditions such as high packet loss rate and long delay. This paper aims at mitigating such effects by leveraging client-side caching proxies. We present a novel cache architecture and associated cache management algorithms that turn edge caches into accelerators of streaming media delivery. This architecture allows partial caching of media objects and joint delivery from caches and origin servers. Most importantly, the caching algorithms are both network-aware and stream-aware; they take into account the popularity of streaming media objects, their bit rate requirements, and the available bandwidth between clients and servers. Using Internet bandwidth models derived from proxy cache logs and measured over real Internet paths, we have conducted extensive simulations to evaluate the performance of various cache management algorithms. Our experiments demonstrate that network-aware caching algorithms can significantly reduce startup delay and improve stream quality. Our experiments also show that partial caching is particularly effective when bandwidth variability is not very high.Shudong Jin: Corespondence to This research was supported in part by NSF (awards ANI-9986397, ANI-0095988, ANI-0205294 and EJA-0202067) and by IBM. Part of this work was done while the first author was at IBM Research in 2001.     

Effective bandwidth based scheduling for streaming media

We propose a class of rate-distortion optimized packet scheduling algorithms for streaming media by generating a number of nested substreams, with more important streams embedding less important ones in a progressive manner. Our goal is to determine the optimum substream to send at any moment in time, using feedback information from the receiver and statistical characteristics of the video. To do so, we model the streaming system as a queueing system, compute the run-time decoding failure probability of a group of picture in each substream based on effective bandwidth approach, and determine the optimum substream to be sent at that moment in time. We evaluate our scheduling scheme with various video traffic models featuring short-range dependency (SRD), long-range dependency (LRD), and/or multifractal properties. From experiments with real video data, we show that our proposed scheduling scheme outperforms the conventional sequential sending scheme.     

流媒体业务中的内容分发技术

内容分发网络是流媒体业务的重要支撑系统，对于提供流媒体业务系统的可扩展性和性能具有重要意义。内容分发技术将流媒体或其它内容迅速有效地分发到网络中靠近用户的边缘部分，使网络用户对内容的访问可以就近得到快速响应，从而大大提高了流媒体业务的服务质量，减轻了源服务器和网络的负载，改善了网络性能，目前已经逐步得到广泛使用。本主要介绍了内容分发网络的产生背景、基本功能、体系结构、业务流程、路由请求机制和发展现状等。     

A dynamic caching algorithm based on internal popularity distribution of streaming media

Most proxy caches for streaming videos do not cache the entire video but only a portion of it. This is partly due to the large size of video objects. Another reason is that the popularity of different parts of a video can be different, e.g., the prefix is generally more popular. Therefore, the development of efficient cache mechanisms requires an understanding of the internal popularity characteristics of streaming videos. This paper has two major contributions. Firstly, we analyze two 6-month long traces of RTSP video requests recorded at different streaming video servers of an entertainment video-on-demand provider, and show that the traces provide evidence that the internal popularity of the majority of the most popular videos obeys a k-transformed Zipf-like distribution. Secondly, we propose a caching algorithm which exploits this empirical internal popularity distribution. We find that this algorithm has similar performance compared with fine-grained caching but requires significantly less state information.     

Analysis of a CDN–P2P hybrid architecture for cost-effective streaming media distribution

To distribute video and audio data in real-time streaming mode, two different technologies – Content Distribution Network (CDN) and Peer-to-Peer (P2P) – have been proposed. However, both technologies have their own limitations: CDN servers are expensive to deploy and maintain, and consequently incur a cost for media providers and/or clients for server capacity reservation. On the other hand, a P2P-based architecture requires sufficient number of seed supplying peers to jumpstart the distribution process. Compared with a CDN server, a peer usually offers much lower out-bound streaming rate and hence multiple peers must jointly stream a media data to a requesting peer. Furthermore, it is not clear how to determine how much a peer should contribute back to the system after receiving the media data, in order to sustain the overall media distribution capacity.In this paper, we propose and analyze a novel hybrid architecture that integrates both CDN- and P2P-based streaming media distribution. The architecture is highly cost-effective: it significantly lowers the cost of CDN capacity reservation, without compromising the media quality delivered. In particular, we propose and compare different limited contribution policies for peers that request a media data, so that the streaming capacity of each peer can be exploited on a fair and limited basis. We present: (1) in-depth analysis of the proposed architecture under different contribution policies, and (2) extensive simulation results which validate the analysis. Our analytical and simulation results form a rigorous basis for the planning and dimensioning of the hybrid architecture.     

PopCap: popularity oriented proxy caching for peer-assisted Internet video-on-demand streaming services

With the success of Internet video-on-demand (VoD) streaming services, the bandwidth required and the financial cost incurred by the host of the video server becoming extremely large. Peer-to-peer (P2P) networks and proxies are two common ways for reducing the server workload. In this paper, we consider a peer-assisted Internet VoD system with proxies deployed at domain gateways. We formally present the video caching problem with the objectives of reducing the video server workload and avoiding inter-domain traffic, and we obtain its optimal solution. Inspired by theoretical analysis, we develop a practical protocol named PopCap for Internet VoD services. Compared with previous work, PopCap does not require additional infrastructure support, is inexpensive, and able to cope well with the characteristic workloads of Internet VoD services. From simulation-based experiments driven by real-world data sets from YouTube, we find that PopCap can effectively reduce the video server workload, therefore provides a superior performance regarding the video server’s traffic reduction.