A performance analysis of an object-based I/O architecture in a video server environment

In this paper, we present a performance analysis of how effective video server applications can be supported on personal computers (PCs) connected through a local area network (LAN). We considered both the standard 16-Mbit/s token ring and a 100-Mbit/s token ring, which follows closely the specifications for the Fiber Distributed Data Interface (FDDI). We examined three I/O architectures for a PC-based video server: an interrupt-driven I/O architecture, a peer-to-peer I/O architecture, and a concurrent, object-based I/O architecture that we proposed. The video server must support multiple MPEG-1 video streams at the same time to multiple clients on the LAN. We found that the network protocol layers require a lot of processing power, and that an implementation of our proposed I/O architecture, which takes advantage of the available power of the host processor to off-load I/O adapters, can deliver much better performance, and is more cost-effective, than other I/O architectures in a video server environment.     

Performance analysis of a peer-to-peer I/O architecture in video server environments

In the personal computing (PC) and workstation environments, more and more I/O adapters are becoming complete functional subsystems that are intelligent enough to handle I/O operations on their own without much intervention from the host processor. The IBM Subsystem Control Block (SCB) architecture has been defined to enhance the potential of these intelligent adapters by defining services and conventions that deliver command information and data to and from the adapters. The SCB architecture has two operating modes. The Locate Mode represents the conventional, interrupt-driven I/O protocol used in many current personal computers. The Move Mode embodies an advanced, peer-to-peer I/O protocol proposed for the next generation of personal computers. In this paper, we would like to discuss and present a performance analysis of the SCB architecture in typical video server environments. In particular, we study a video server capable of providing support for simultaneous MPEG-1 video streams to multiple clients on a 16-Mbps token-ring network. We also consider the performance impact of a hypothetical 100-Mbps token-ring technology on the video server performance.     

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     

Collaborative caching for efficient dissemination of personalized video streams in resource constrained environments

The ever increasing deployment of broadband networks and simultaneous proliferation of low-cost video capturing and multimedia-enabled mobile devices such as smart cellular phones, netbook computers, and tablet computers have triggered a wave of novel mobile multimedia applications making video streaming on mobile devices increasingly popular and commonplace. Networked environments consisting of mobile devices tend to be highly heterogeneous in terms of client-side and system-wide resource constraints, clients’ queries for information, geospatial distribution, and dynamic trajectories of the mobile clients, and client-side and server-side privacy and security requirements. Invariably, the video streams need to be personalized to provide a resource-constrained mobile device with video content that is most relevant to the client’s request while simultaneously satisfying the client-side and system-wide resource constraints, privacy and security requirements and the constraints imposed by the geospatial distribution and dynamic trajectories of the mobile clients relative to the server(s). In this paper, we present the design and implementation of a distributed system, consisting of several geographically distributed video personalization servers and proxy caches, for efficient dissemination of personalized video in a resource-constrained mobile environment. With the objective of optimizing cache performance, a novel cache replacement policy and multi-stage client request aggregation strategy, both of which are specifically tailored for personalized video content, are proposed. A novel Latency-Biased Collaborative Caching (LBCC) protocol based on counting Bloom filters is designed for further enhancing the scalability and efficiency of disseminating personalized video content. The benefits and costs associated with collaborative caching for disseminating personalized video content to resource-constrained and geographically distributed clients are analyzed and experimentally verified. The impact of different levels of collaboration among the caches and the advantages of using multiple video personalization servers with varying degrees of mirrored content on the efficiency of personalized video delivery are also studied. Experimental results demonstrate that the proposed collaborative caching scheme, coupled with the proposed personalization-aware cache replacement and client request aggregation strategies, provides a means for efficient dissemination of personalized video streams in resource-constrained environments.     

Dynamic batching policies for an on-demand video server

In a video-on-demand environment, continuous delivery of video streams to the clients is guaranteed by sufficient reserved network and server resources. This leads to a hard limit on the number of streams that a video server can deliver. Multiple client requests for the same video can be served with a single disk I/O stream by sending (multicasting) the same data blocks to multiple clients (with the multicast facility, if present in the system). This is achieved by batching (grouping) requests for the same video that arrive within a short time. We explore the role of customer-waiting time and reneging behavior in selecting the video to be multicast. We show that a first come, first served (FCFS) policy that schedules the video with the longest outstanding request can perform better than the maximum queue length (MQL) policy that chooses the video with the maximum number of outstanding requests. Additionally, multicasting is better exploited by scheduling playback of the most popular videos at predetermined, regular intervals (hence, termed FCFS-). If user reneging can be reduced by guaranteeing that a maximum waiting time will not be exceeded, then performance of FCFS- is further improved by selecting the regular playback intervals as this maximum waiting time. For an empirical workload, we demonstrate a substantial reduction (of the order of 60%) in the required server capacity by batching.     

一种基于节的视频服务器允许接纳控制算法

提出了一种基于“服务器节”的支持压缩多媒体流的服务器中CPU、磁盘、网络和内存等资源管理的方法和允许接纳控制算法。“服务器节”概念定义了一组客户视频服务特性,如播放、快进、慢进和暂停等,并且确定了视频服务所需资源的分配参。一个“服务器节”包括视频服务器、磁盘设备、网络设备和允许接纳控制。它不但能优化使用单个资源,对于给定系统支持最大数量的客户端,保证其服务质量（QoS),而且其允许接纳控制算法能根据系统所有资源的状况,在不影响原有的视频服务基础上,确定对客户端新提出的视频服务是否接受。     

Periodic broadcast and patching services - implementation,measurement and analysis in an internet streaming video testbed

Multimedia streaming applications can consume a significant amount of server and network resources. Periodic broadcast and patching are two approaches that use multicast transmission and client buffering in innovative ways to reduce server and network load, while at the same time allowing asynchronous access to multimedia streams by a large number of clients. Current research in this area has focussed primarily on the algorithmic aspects of these approaches, with evaluation performed via analysis or simulation. In this paper, we describe the design and implementation of a flexible streaming video server and client test bed that implements both periodic broadcast and patching, and explore the issues that arise when implementing these algorithms using laboratory and internet-based test beds. We present measurements detailing the overheads associated with the various server components (signaling, transmission schedule computation, data retrieval and transmission), the interactions between the various components of the architecture, and the overall end-to-end performance. We also discuss the importance of an appropriate server application-level caching policy for reducing the needed disk bandwidth at the server. We conclude with a discussion of the insights gained from our implementation and experimental evaluation.Subhabrata Sen: The work of this author was conducted while he was at the University of Massachusetts.     

Searching and editing MPEG-compressed video in a distributed online environment

WebClip (on-line demo at http://www.ctr.columbia.edu/webclip) is a compressed video searching and editing system operating over the World Wide Web. WebClip uses a distributed client-server model including a server engine for content analysis/editing, and clients for interactive controls of video browsing/editing. It specializes several unique features, including compressed-domain video feature extraction and manipulation, multi-resolution video access, content based video browsing/retrieval, and a distributed network architecture.     

A video caching policy for providing differentiated service grades and maximizing system revenue in hierarchical video servers

A video server normally targets at providing abundant bandwidth access and massive storage in supporting large-scale video archival applications. Its performance is sensitive to the deployment of the stored contents. In this paper, we propose a video caching policy for a video server, based on the knowledge of video profiles, namely: access rate, video size and bandwidth, tolerable rejection probability, and rental price. We consider the video server as having a hierarchical architecture which consists of a set of high-speed disk drives located in the front end for caching a subset of videos, and another set of high-capacity tertiary devices located in the back end for archiving the entire video collection. The front-end disks particularly, are organized together by employing a proposed data striping scheme, termed the adaptive striping (AS), which is flexible on heterogeneous disk integration. The proposed policy determines what video set should be cached, and how to arrange them in the front-end disks with two objectives in mind: (1) offering differentiated service grades conforming to the video profiles as well as (2) maximizing the overall system revenue. We simulate the system with various configurations, and the results affirm our effective approach.     

Comparison of in-network versus Staggered Multicast video distribution models

This paper proposes a new video distribution service: Video-In-Network (VIN). In VIN, videos are continuously circulating in an optical network where they can be easily retrieved by VIN Nodes. A mathematical model of the VIN system was derived and used to explore the performance of VIN in terms of the maximum number of concurrent video streams which can be supported by the system. We then compared VIN with Staggered Multicast. We found that VIN has a number of advantages over Staggered Multicast. First, VIN is more scalable in terms of the number of streams/channels. Second, the startup latency of VIN is shorter than that of Staggered Multicast. Third, Staggered Multicast is a near-VOD system and the video clients usually have no specific channels to the server to request for video. In the VIN system, the video clients can request the VIN Node for particular videos for multicast or unicast on demand.     

Design a progressive video caching policy for video proxy servers

Proxy servers have been used to cache web objects to alleviate the load of the web servers and to reduce network congestion on the Internet. In this paper, a central video server is connected to a proxy server via wide area networks (WANs) and the proxy server can reach many clients via local area networks (LANs). We assume a video can be either entirely or partially cached in the proxy to reduce WAN bandwidth consumption. Since the storage space and the sustained disk I/O bandwidth are limited resources in the proxy, how to efficiently utilize these resources to maximize the WAN bandwidth reduction is an important issue. We design a progressive video caching policy in which each video can be cached at several levels corresponding to cached data sizes and required WAN bandwidths. For a video, the proxy server determines to cache a smaller amount of data at a lower level or to gradually accumulate more data to reach a higher level. The proposed progressive caching policy allows the proxy to adjust caching amount for each video based on its resource condition and the user access pattern. We investigate the scenarios in which the access pattern is priorly known or unknown and the effectiveness of the caching policy is evaluated.     

Context-dependent software solutions to handle video synchronization and delay in collaborative live mobile video production

The advent of modern mobile phones, 3G networks, and live video streaming has made it possible to broadcast live video from mobile devices. This is now giving rise to a new class of applications which enable mobile collaborative live video production, in which groups of amateurs work together to provide a rich broadcast of events. We focus on new and expected synchronization problems that arise in these more complex systems when broadcasting live events because of the delays that often occur in streaming over internet and mobile networks. The problem has been investigated by acquiring initial user feedback, as well as conducting technical delay measurements of two examples of such systems and relating them to existing literature. We identified two types of technical problems which affect the mixing of the streams, namely the difference in delay in multiple streams, a.k.a. asynchrony among streams, and the delay between the event itself and its presentation in the mixer. These problems affect the mixing in various ways depending on whether or not the director has visual access to the unmediated event. This knowledge has then been used to inform the conceptualization of identifiable ways of handling delays and synchronization. We suggest the introduction of a software feature providing context-dependent delay, in which these requirements can be balanced differently to fit specific contexts of use. We specifically address the different types of mixing which occurs when the director, or mixer, only has access to the topic through the mobile media (“out of view”), as well as mixing in a context in which the topic also is physically present (“in-view”) in front of the mixer.     

A scalable cost-effective video broadcasting system for on-demand video services

Recent years have seen intensive investigations of Periodic Broadcast, an attractive paradigm for broadcasting popular videos. In this paradigm, the server simply broadcasts segments of a popular video periodically on a number of communication channels. A large number of clients can be served simultaneously by tuning into these channels to receive segments of the requested video. A playback can begin as soon as a client can access the first segment. Periodic Broadcast guarantees a small maximum service delay regardless of the number of concurrent clients. Existing periodic broadcast techniques are typically evaluated through analytical assessment. While these results are good performance indicators, they cannot demonstrate subtle implementation difficulty that can prohibit these techniques from practical deployment. In this paper, we present the design and implementation of a video broadcasting system based on our periodic broadcast scheme called Striping Broadcast. Our experience with the system confirms that the system offers a low service delay close to its analytical guaranteed delay while requiring small storage space and low download bandwidth at a client.     

Arrangement of multi-dimensional scalable video data for heterogeneous clients

A scalable video server extracts data corresponding to the resolution requested by its client from the total data containing the information encoding a full resolution video. Depending on the requested resolution, the extracted data may not be contiguously placed on a disk or a disk array. For this reason, the traverse distance, which indicates the difference between the first read position and the last read position, can be much larger than the amount of the requested data. This causes additional rotational latency in a disk and thus degrades disk performance. Furthermore, scalable video data more seriously deteriorates the independency of disks in a disk array. That is, even a small read request can be split into multiple disk requests across disks of a disk array, because the requested data are scattered across multiple disks. To address these problems, we propose new data arrangement schemes for scalable video data. In these new schemes, we first deal with the arrangement of multi-dimensional scalable video data, which can be employed regardless of the number of scalability dimensions. Second, we improve disk performance by reducing average disk cost, which is based on both the traverse distance of each disk and the independency of disks. Third, we improve overall performance of disk devices through considering the entire request pattern, when large numbers of clients concurrently demand heterogeneous resolutions of videos from a server. We also propose fast arrangement algorithms to reduce the computation time required for searching an effective arrangement so that they can be easily applied to practical server system.     

Reducing bandwidth requirement for delivering video over wide area networks with proxy server

Due to the high bandwidth requirement and rate variability of compressed video, delivering video across wide area networks (WANs) is a challenging issue. Proxy servers have been used to reduce network congestion and improve client access time on the Internet by caching passing data. We investigate ways to store or stage partial video in proxy servers to reduce the network bandwidth requirement over WAN. A client needs to access a portion of the video from a proxy server over a local area network (LAN) and the rest from a central server across a WAN. Therefore, client buffer requirement and video synchronization are to be considered. We study the tradeoffs between client buffer, storage requirement on the proxy server, and bandwidth requirement over WAN. Given a video delivery rate for the WAN, we propose several frame staging selection algorithms to determine the video frames to be stored in the proxy server. A scheme called chunk algorithm, which partitions a video into different segments (chunks of frames) with alternating chunks stored in the proxy server, is shown to offer the best tradeoff. We also investigate an efficient way to utilize client buffer when the combination of video streams from WAN and LAN is considered.     

Practical algorithms for scheduling video data in a local area network environment

Simultaneous transmission of multiple high quality video streams from a server to the clients is becoming an increasingly important class of traffic in a network of workstations or cluster environment. With a powerful symmetric multiprocessor (SMP) as the server and a high-speed network, such transmission is practicable from a hardware point of view. However, the actual construction of such a video data server system entails tackling a number of difficult problems related to the provision of strict quality of service (QoS) guarantees. Among others, the smoothing and scheduling of multiple video packet streams are two crucial issues. Smoothing is concerned with reducing the rate variability of video streams in view of the fact that video data are usually compressed in a variable bit rate fashion. Scheduling is important to guarantee the requested QoS levels while maximizing the utilization of the resources. Although much work on smoothing has been done, it is not clear which scheduling scheme is suitable for multiplexing smoothed video data to the network. In this paper we present an extensive performance study of the EDF and RM scheduling algorithms which are modified to provide QoS guarantees for smoothed video data. With a probabilistic definition of QoS, admission control conditions are incorporated into the two algorithms. Furthermore, a counter-based scheduling module is included as the core scheduling mechanism which adaptively adjusts the actual QoS levels assigned to requests. Our theoretical analysis of the two modified algorithms, called QEDF and QRM, shows that the QRM algorithm is more robust than the QEDF algorithm for different workload and utilization conditions. We also propose to use a new metric called meta-QoS to quantify the overall performance of a packet scheduler given a set of simultaneous requests. In our experiments based on an SMP-based Linux platform, we find that the QRM algorithm can sustain a rather stable level of meta-QoS even when the workload and utilization levels are increased. On the other hand, the QEDF algorithm, due to its conservative admission control policy, is found to be not suitable for a high level of utilization and a large number of requests. In view of the lower complexity of the QRM algorithm, it seems that the QRM approach is a more suitable candidate for packet scheduling in the client-server environment considered in our study.

Multipath routing and rate-controlled video encoding in wireless video surveillance networks

Video surveillance systems typically consist of many video sources distributed over a wide area, transmitting live video streams to a central location for processing and monitoring. The target of this paper—to bring down the overall system cost and increase feasibility, scalability, and performance—is to propose a new architecture for a wireless video surveillance network, whose telecommunication infrastructure is based on a wireless mesh network, and where video sources are able to estimate network bandwidth and consequently control their output rate. Multipath routing is applied in such a way that at least part of the information arrives at its destination even if a wireless link is shielded (maliciously or not). A case study is considered to discuss the performance of the proposed architecture, analyzing a comparison between single-path and multipath approaches.     

QoS-aware service composition for distributed video surveillance

Quality of Service (QoS) is essential for the ubiquitous access of media services in real-time distributed video surveillance applications. To have ubiquitous access of desired media with emergency officials’ handheld devices, appropriate media transcoding services are required. Currently, it is challenging to select and compose these services for each of the devices to satisfy the desired QoS demand. To compose these media services so that video stream is available for target pervasive and smart devices, a composition algorithm is required. Thus, this paper presents a QoS-aware service composition algorithm to select the best composition for the target ubiquitous client so that it can optimally provide QoS to heterogeneous users. We have implemented a video surveillance prototype to demonstrate the performance of the proposed QoS-aware composition algorithm. Results from this prototype reveal that the approach is suitable for real-time video surveillance.     

Design and evaluation of a generic software architecture foron-demand video servers

Introduces the design, implementation and evaluation of a generic software architecture for on-demand video servers. We describe different key components for controlling the storage and network devices within the server. The interactive collaborations between these software components are also illustrated. The experimental results indicate a very promising direction in exploring the right combinations of these software components. The server is thus able to increase the number of concurrent video accesses with the same hardware configuration. For instance, with the right combinations, the system achieved about 80% of the storage system bandwidth of four disks, about 70% of the storage system bandwidth of six disks, and generally reached the maximal achieved SCSI bandwidth when eight disks are used over two SCSI buses. Our research and experimental results are based on video servers currently under construction across a variety of hardware platforms, including SMP, DMP and clusters of PCs or workstations. The most advanced prototype server is based on an SGI shared-memory multiprocessor with a mass storage system consisting of RAID-3 disk arrays. With all the enabling/management schemes, we were able to further investigate interesting research issues by considering the user's access profiles for taking advantage of popular video titles. The results were significant, with a range of 60% improvement given a 512 kByte block size. In addition to the experimental results, theoretical performance models were also developed that closely match to our collected experimental results     

Peer-assisted adaptation in periodic broadcasting of videos for heterogeneous clients

The increasing use of streaming applications and wide variety of devices, such as handheld personal organizers, have raised new challenges, such as the provision of access to multimedia content for devices with limited computing and bandwidth capabilities. In this paper, we propose a technique for periodic broadcasting. Our technique allows clients with low bandwidth capability to be served in the same period as high-bandwidth clients, using peer-to-peer streaming between clients, and also works for clients with downstream capability below the video bit rate. In the proposed system, the server builds multicast trees of clients that allow clients with low bandwidth to be served by other clients with sufficient upstream bandwidth. Clients below the video bit rate will suffer additional, but only moderately noticeable, delays that occur as video is converted to lower quality. We performed extensive simulation and showed that our system can provide improved service performance for heterogeneous clients on periodic broadcasting protocols.