Dynamic Scheme Transition Adaptable to Variable Video Popularity in a Digital Broadcast Network

To provide on-demand video streaming services through the network, video objects with both high and low client request rates must be served efficiently. In this paper, we propose a dynamic scheme transition to provide on-demand streaming services efficiently regardless of video popularity. This approach can maintain quality-of-service (QoS) by transitioning the service scheme according to the request rate. The server provides services by heuristically broadcasting video segments when the video popularity is low and by a Periodic Broadcast when the video popularity is high. The server identifies the variations in client request rates from the number of service channels and determines transitions to more efficient service schemes autonomously. We evaluated this scheme transition for various parameters and traces from a company providing streaming services. The results show that the performance of scheme transition is very efficient.      

The Analysis and Performance of Multi-Rate Service in Distributed Video-on-Demand Systems

In this paper, we develop an end-to-end analysis of a distributed Video-on-Demand (VoD) system that includes an integrated model of the server and the network subsystems with analysis of its impact on client operations. The VoD system provides service to a heterogeneous client base at multiple playback rates. A class-based service model is developed where an incoming video request can specify a playback rate at which the data is consumed on the client. Using an analytical model, admission control conditions at the server and the network are derived for multi-rate service. We also develop client buffer requirements in presence of network delay bounds and delay jitter bounds using the same integrated framework of server and network subsystems. Results from an extensive simulation show that request handling policies based on limited redirection of blocked requests to other resources perform better than load sharing policies. The results also show that downgrading the service for blocked requests to a lower bitrate improves VoD system performance considerably. Combining the downgrade option with restrictions on access to high bitrate request classes is a powerful tool for manipulating an incoming request mix into a workload that the VoD system can handle.     

基于QoS的磁盘调度策略

随着视频点播、视频会议、视频监控、数字图书馆等流媒体应用的普及，流媒体服务器存储资源管理成为制约服务质量的瓶颈之一。根据多媒体服务器的性能要求，提出了一种支持QoS的磁盘调度策略。它由三个主要部分组成：探测模块、负载监测模块和自适应管理模块。探测模块，负责判断当前的资源情况能否满足服务请求；自适应模块，根据负载监删模块检测到的负载变化情况，动态调整服务周期在实时请求和尽力服务请求之间的分配。实验表明此磁盘调度策略能在保证实时请求无抖动执行的同时，明显减少了非实时请求的响应时间。     

Design and analysis of a video-on-demand server

The availability of high-speed networks, fast computers and improved storage technology is stimulating interest in the development of video on-demand services that provide facilities similar to a video cassette player (VCP). In this paper, we present a design of a video-on-demand (VOD) server, capable of supporting a large number of video requests with complete functionality of a remote control (as used in VCPs), for each request. In the proposed design, we have used an interleaved storage method with constrained allocation of video and audio blocks on the disk to provide continuous retrieval. Our storage scheme interleaves a movie with itself (while satisfying the constraints on video and audio block allocation. This approach minimizes the starting delay and the buffer requirement at the user end, while ensuring a jitter-free display for every request. In order to minimize the starting delay and to support more non-concurrent requests, we have proposed the use of multiple disks for the same movie. Since a disk needs to hold only one movie, an array of inexpensive disks can be used, which reduces the overall cost of the proposed system. A scheme supported by our disk storage method to provide all the functions of a remote control such as “fast-forwarding”, “rewinding” (with play “on” or “off”), “pause” and “play” has also been discussed. This scheme handles a user request independent of others and satisfies it without degrading the quality of service to other users. The server design presented in this paper achieves the multiple goals of high disk utilization, global buffer optimization, cost-effectiveness and high-quality service to the users.     

Harmonic proportional bandwidth allocation and scheduling for service differentiation on streaming servers

To provide ubiquitous access to the proliferating rich media on the Internet, scalable streaming servers must be able to provide differentiated services to various client requests. Recent advances of transcoding technology make network-I/O bandwidth usages at the server communication ports controllable by request schedulers on the fly. In this article, we propose a transcoding-enabled bandwidth allocation scheme for service differentiation on streaming servers. It aims to deliver high bit rate streams to high priority request classes without overcompromising low priority request classes. We investigate the problem of providing differentiated streaming services at application level in two aspects: stream bandwidth allocation and request scheduling. We formulate the bandwidth allocation problem as an optimization of a harmonic utility function of the stream quality factors and derive the optimal streaming bit rates for requests of different classes under various server load conditions. We prove that the optimal allocation, referred to as harmonic proportional allocation, not only maximizes the system utility function, but also guarantees proportional fair sharing between classes with different prespecified differentiation weights. We evaluate the allocation scheme, in combination with two popular request scheduling approaches, via extensive simulations and compare it with an absolute differentiation strategy and a proportional-share strategy tailored from relative differentiation in networking. Simulation results show that the harmonic proportional allocation scheme can meet the objective of relative differentiation in both short and long timescales and greatly enhance the service availability and maintain low queueing delay when the streaming system is highly loaded.     

Performance analysis of a pull-based parallel video server

In conventional video-on-demand systems, video data are stored in a video server for delivery to multiple receivers over a communications network. The video server's hardware limits the maximum storage capacity as well as the maximum number of video sessions that can concurrently be delivered. Clearly, these limits will eventually be exceeded by the growing need for better video quality and larger user population. This paper studies a parallel video server architecture that exploits server parallelism to achieve incremental scalability. First, unlike data partition and replication, the architecture employs data striping at the server level to achieve fine-grain load balancing across multiple servers. Second, a client-pull service model is employed to eliminate the need for interserver synchronization. Third, an admission-scheduling algorithm is proposed to further control the instantaneous load at each server so that linear scalability can be achieved. This paper analyzes the performance of the architecture by deriving bounds for server service delay, client buffer requirement, prefetch delay, and scheduling delay. These performance metrics and design tradeoffs are further evaluated using numerical examples. Our results show that the proposed parallel video server architecture can be linearly scaled up to more concurrent users simply by adding more servers and redistributing the video data among the servers     

Loopback: exploiting collaborative caches for large-scale streaming

In this paper, we propose a Loopback approach in a two-level streaming architecture to exploit collaborative client/proxy buffers for improving the quality and efficiency of large-scale streaming applications. At the upper level we use a content delivery network (CDN) to deliver video from a central server to proxy servers. At the lower level a proxy server delivers video with the help of collaborative client caches. In particular, a proxy server and its clients in a local domain cache different portions of a video and form delivery loops. In each loop, a single video stream originates at the proxy, passes through a number of clients, and finally is passed back to the proxy. As a result, with limited bandwidth and storage space contributed by collaborative clients, we are able to significantly reduce the required network bandwidth, I/O bandwidth, and cache space of a proxy. Furthermore, we develop a local repair scheme to address the client failure issue for enhancing service quality and eliminating most required repairing load at the central server. For popular videos, our local repair scheme is able to handle most of single-client failures without service disruption and retransmissions from the central server. Our analysis and simulations have shown the effectiveness of the proposed scheme.     

面向智能电子商务的移动Agent迁移策略研究

以智能电子商务系统为应用研究背景,综合考虑商家服务质量、网络负载等影响查询效率的因素,引入时间片概念,提出了一种基于商品智能搜索的Agent迁移策略模型。在模型中给出了一种客观准确的商家服务质量评价方法,采用申请与应答的方式有效避免了因网络负载和商家服务器负载等原因造成的迁移失败的问题,同时减少了网络带宽和服务器资源的浪费。     

A Design Framework for Multi-Resolution Video Servers

Video can be encoded into multiple-resolution format in nature. A multi-resolution or scalable video stream is a video sequence encoded such that subsets of the full resolution video bit stream can be decoded to recreate lower resolution video streams. Employing scalable video enables a video server to provide multiple resolution services for a variety of clients with different decoding capabilities and network bandwidths connected to the server. The inherent advantages of the multi-resolution video server include: heterogeneous client support, storage efficiency, adaptable service, and interactive operations support.For designing a video server, several issues should be dealt with under a unified framework including data placement/retrieval, buffer management, and admission control schemes for deterministic service guarantee. In this paper, we present a general framework for designing a large-scale multi-resolution video server. First, we propose a general multi-resolution video stream model which can be implemented by various scalable compression techniques. Second, given the proposed stream model, we devise a hybrid data placement scheme to store scalable video data across disks in the server. The scheme exploits both concurrency and parallelism offered by striping data across the disks and achieves the disk load balancing during any resolution video service. Next, the retrieval of multi-resolution video is described. The deterministic access property of the placement scheme permits the retrieval scheduling to be performed on each disk independently and to support interactive operations (e.g. pause, resume, slow playback, fastforward and rewind) simply by reconstructing the input parameters to the scheduler. We also present an efficient admission control algorithm which precisely estimates the actual disk workload for the given resolution services and hence permits the buffer requirement to be much smaller. The proposed schemes are verified through detailed simulation and implementation.     

VoD系统中基于优先级的准入控制和带宽分配策略

本文针对VoD系统中不同客户对视频服务质量的不同要求,提出一种基于优先级的准入控制和带宽动态分配策略。在准入控制时,综合考虑请求的优先级和并发流占用的实际带宽等因素,在保证为高优先级请求预留较多固定带宽的同时提高并发流个数;在服务过程中,根据优先级和网络状况动态调整每个流的带宽,使丢包率低于一定的阈值,并保证在相同的网络状态下为高优先级请求提供较高的视频服务质量。     

A speculative load adaptive streaming scheme for efficient video delivery

Video on demand services require video broadcast schemes to provide efficient and reliable performance under various client request loads. In this paper, we have developed an efficient request load adaptive broadcast scheme, speculative load adaptive streaming scheme (SLAS), that requires lower service bandwidth than previous approaches, regardless of request rate. We have provided both analysis and simulation to show the performance gain over previous schemes. In this paper, we provide the theoretic upper bound of the continuous segment allocations on channels. We found that the number of allocated segments of the SLAS is close to the theoretic upper bound when compared with other schemes over various numbers of stream channels. Our analysis of client waiting time is almost identical to simulation results about all client requests. By simulation, we compared the required service bandwidth and storage requirements of the SLAS scheme and other schemes and found the SLAS scheme is an efficient broadcast scheme as compared to well known seamless channel transition schemes.     

OCS: An effective caching scheme for video streaming on overlay networks

Video streaming is vital for many important applications such as distance learning, digital video libraries, and movie-on-demand. Since video streaming requires significant server and networking resources, caching has been used to reduce the demand on these resources. In this paper, we propose a novel collaboration scheme for video caching on overlay networks, called Overlay Caching Scheme (OCS), to further minimize service delays and loads placed on an overlay network for video streaming applications. OCS is not a centralized nor a hierarchical collaborative scheme. Despite its design simplicity, OCS effectively uses an aggregate storage space and capability of distributed overlay nodes to cache popular videos and serve nearby clients. Moreover, OCS is light-weight and adaptive to clients’ locations and request patterns. We also investigate other video caching techniques for overlay networks including both collaborative and non-collaborative ones. Compared with these techniques on topologies inspired from actual networks, OCS offers extremely low average service delays and approximately half the server load. OCS also offers smaller network load in most cases in our study.

使用特殊复合距离的选播路由算法

选播成员都是等价的服务器,服务数据的服务质量比作为请求的选播数据报更为重要．使用特殊复合距离的选播路由算法(ASCD)使用跳数、逆向传输延迟、逆向可用带宽以及服务器负载合成的距离来选择路径．不同于其他算法,ASCD使用度量在路径逆向上的值,即从选播数据报目标节点(服务器)到选播数据报源节点(客户)方向,而不是常规从选播数据报的源节点到目的节点方向．ASCD定位的路径和选播成员使选播数据报请求的服务数据能够得到更多路径资源．ASCD还能够在一定程度上平衡服务器负载．     

Web服务器系统中基于反馈控制的比例延迟保证

随着Web应用在商业领域的广泛使用,Web服务器系统需要在高负载下提供区分服务,以满足用户的不同需求。为实现以延迟作为评价指标的区分服务,本文在Web服务器系统的连接管理和请求处理两个层次建立了基于反馈控制的比例延迟保证模型。模型中的反馈控制器通过动态计算和调节不同类别客户占用的资源：（服务线程和数据库连接）,能保证高优先级的客户较快得到服务而不同类别客户的平均延迟比保持不变。为测试闭环系统的性能,设计了两种分别服从均匀分布和重尾分布的动态负载。仿真结果表明,即使并发客户连接的数目剧烈变化,控制器作用下的服务器系统仍然能够达到较好的比例延迟保证,可靠地为用户提供区分服务。     

基于QoS延时参数的服务接纳控制算法

为给并发访问的多个请求提供QoS保证,Web Service必须借助某些算法对请求加以控制。该文分析QoS延时参数的构成,提出基于QoS延时参数的服务接纳控制算法。该算法可在满足既有服务的QoS延时要求的条件下,控制接纳新进入的服务。否则即让其在队列中等待直到被服务器接纳,或服务器直接抛弃这个请求,由客户端在超时后自动重发请求。     

无线城域网中MPEG视频传输的上行调度算法

针对现有无线城域网中MPEG视频传输的实时轮询服务算法的不足,提出了一种更为有效的媒体接入控制上行调度算法。该算法无需基站周期地提供带宽请求机会,而是在视频应用的连接建立以后,主动周期地分配固定带宽来传输视频数据的特定部分,剩余部分的带宽通过携带请求的方式获得,以此保证更好的服务质量。仿真中使用典型的视频测试源,结果表明,新算法在近似现有算法的信道利用率的情况下,具有更小的视频帧延迟和抖动。     

Optimal server allocations for streaming multimedia applications on the Internet

In this paper, we address the server selection problem for streaming applications on the Internet. The architecture we consider is similar to the content distribution networks consisting of geographically dispersed servers and user populations over an interconnected set of metropolitan areas. Server selection issues for Web-based applications in such an environment have been widely addressed; the selection is mostly based on proximity measured using packet delay. Such a greedy or heuristic approach to server selection will not address the capacity planning problem evident in multimedia applications. For such applications, admission control becomes an essential part of their design to maintain Quality of Service (QoS). Our objective in providing a solution to the server selection problem is threefold: first, to direct clients to the nearest server; second, to provide multiple sources to diffuse network load; third, to match server capacity to user demand so that optimal blocking performance can be expected. We accomplish all three objectives by using a special type of Linear Programming (LP) formulation called the Transportation Problem (TP). The objective function in the TP is to minimize the cost of serving a video request from user population x using server y as measured by network distance. The optimal allocation between servers and user populations from TP results in server clusters, the aggregated capacity of each cluster designed to meet the demands of its designated user population. Within a server cluster, we propose streaming protocols for request handling that will result in a balanced load. We implement threshold-based admission control in individual servers within a cluster to enforce the fair share of the server resource to its designated user population. The blocking performance is used as a trigger to find new optimal allocations when blocking rates become unacceptable due to change in user demands. We substantiate the analytical model with an extensive simulation for analyzing the performance of the proposed clustered architecture and the protocols. The simulation results show significant difference in overall blocking performance between optimal and suboptimal allocations in as much as 15% at moderate to high workloads. We also show that the proposed cluster protocols result in lower packet loss and latencies by forcing path diversity from multiple sources for request delivery.     

支持视频广播的SIP媒体服务器设计与实现

SIP协议是由IETF开发的一个新的非常有前途的VOIP信令协议，而媒体服务也是近几年比较热门的技术话题，本文针对向网络用户提供基于SIP协议视频广播服务这一要求，探讨了实现这一服务所需的关键技术，然后设计了媒体服务器的协议分层模型和媒体服务器的体系结构，最终根据所设计的体系结构实现了一个支持视频广播服务的原型系统。     

Traffic Prediction for Reliable and Resilient Video Communications Over Multi-Location WMNs

This paper studies reliable and resilient deployment of video over IP across a multi-location organization, where a number of wireless mesh network (WMN) clouds are connected by a virtual private network (VPN). Particularly, we propose a scheme of enhanced SIP proxy server which can support an accountable network. In our proposed solution, the enhanced SIP proxy server consists of three modules, namely traffic load prediction, VPN bandwidth negotiation, and call admission control (CAC) in order to provide trustable service. We identify traffic load prediction as the key component among the three modules, and we further develop a linear predictor of variable sampling rate-normalized least mean square (VSR-NLMS) to estimate the traffic patterns. VSR-NLMS predictor employs adjustable sampling rate to achieve improved efficiency and performance. Numerical results show that our proposed scheme can automatically choose suitable sampling rate to track and predict the traffic load curve with acceptable accuracy and reasonable computational complexity.