Access Time Minimization for Distributed Multimedia Applications

The problem of minimizing the access time of a requested multimedia (MM) document on a network based environment is addressed. A generalized version of this problem is formulated and retrieval strategies that minimize the access time of the user-requested MM document from a pool of MM servers are proposed. To this end, we design single-installment and multi-installment MM document retrieval strategies, through which the minimization of access time can be carried out. The main idea is to utilize more than one MM server in downloading the requested document. Each server assumes the responsibility of uploading a predetermined portion of the entire document in a particular order. Single- and multi-installment strategies differ in the number of disjoint document pieces each server sends to the client. We first introduce a directed flow graph (DFG) model to represent the retrieval process and generate a set of recursive equations using this DFG. Then, we derive closed-form solutions for the portions of the MM document downloaded from the various servers and the corresponding access time. We present rigorous analysis for these two strategies and show their performance under MPEG-I and MPEG-II video streams playback rates. Their behavior under different network bandwidths is also examined, revealing in-depth information about their expected performance. We also show that in the case of a multi-installment strategy, the access time can be completely controlled by fine tuning the number of installments. Since the number of installments is software tunable, the adaptive nature of the strategies to different channel bandwidths is also demonstrated. Important trade-off studies with respect to the number of servers involved in the retrieval process and the number of installments are presented. In the case of a heterogeneous network employing a single-installment strategy, we prove that the access time is independent of the server sequence used. Illustrative examples are provided for ease of understanding.     

Efficient Movie Retrieval Strategies for Movie-on-Demand Multimedia Services on Distributed Networks

In this paper, for a network-based multimedia Video/Movie-on-demand(VoD/MoD) service, we design and analyze efficient retrieval strategies to minimize both the access times of the movies and the block rates. We consider a heterogeneous set of servers and a generic network topology in which clients can request for movies from any site. We design and analyze a multiple servers retrieval strategy (MSRS) to retrieve the movies requested by the clients and present a rigorous analysis on its performance with respect to access times of the requested movies and the block rates. A generalized approach of MSRS is designed in a judicious manner using a two-step approach. In the first step, we partition the available bandwidth among the requested movies and in the second step, we derive optimal portions of the movies to be retrieved from each of the servers for each movie, based on allocated bandwidths in the first step. Thus, with the optimal playback portions of the movies using aggregate retrieval bandwidth from several servers, the access times of the movies are minimized. In the first step, in addition to the access times, we minimize the block rates by balancing the total accesses/requests among the servers. In generating the retrieval schedule, our scheme utilizes the available bandwidth (resource) among the servers and guarantees to use less buffer space than a single server retrieval strategy (SSRS). With this two-step approach, a complete flexibility is provided in tuning the access times of the movies and also shown to be robust to any variations in the user access rates of the movies, in reality. Rigorous simulation experiments are presented to observe the performance of MSRS with respect to some important system dependent parameters. Comparing with SSRS, MSRS shows better performance in the simulation.     

Multiple-server movie-retrieval strategies for distributed multimedia applications: a play-while-retrieve approach

In this paper, we present a generalized approach to retrieve a long-duration movie requested using a network-based video-on-demand service infrastructure employing multiple servers. We design and analyze a play-while-retrieve (PWR) playback strategy for this multiserver environment such that the access time (waiting time for the clients) is minimized. For this strategy, we use both the single-installment and multi-installment retrieval strategies to analyze the performance of the service system. For the above-mentioned retrieval strategies, we explicitly derive closed-form expressions for a minimum access time. For the case of multi-installment retrieval strategy, we conduct asymptotic performance analysis that quantifies the ultimate performance bounds of our strategy. We demonstrate analytically the impact of a large-scale network, as well as the impact of indefinitely increasing the number of installments, on the performance of such a multiserver service system. We then address the problem of buffer management at the client site, which is a closely related issue that has a significant influence on the performance of the strategy, and also serves as a key issue in making the service system attractive for clients. We derive relationships that quantify the minimum amount of buffer expected at the client site to have a smooth presentation with this multiserver service structure. Finally, we perform simulation experiments to verify all our theoretical findings. In the experiments, we compare the performance of PWR strategy with that of play-after-retrieve strategy, and discuss certain important points that are crucial for implementing a real-life working multiserver service system.     

Presentation planning for distributed VoD systems

A distributed video-on-demand (VoD) system is one where a collection of video data is located at dispersed sites across a computer network. In a single site environment, a local video server retrieves video data from its local storage device. However, in distributed VoD systems, when a customer requests a movie from the local server, the server may need to interact with other servers located across the network. In this paper, we present different types of presentation plans that a local server can construct in order to satisfy a customer request. Informally speaking, a presentation plan is a temporally synchronized sequence of steps that the local server must perform in order to present the requested movie to the customer. This involves obtaining commitments from other video servers, obtaining commitments from the network service provider, as well as making commitments of local resources, while keeping within the limitations of available bandwidth, available buffer, and customer data consumption rates. Furthermore, in order to evaluate the quality of a presentation plan, we introduce two measures of optimality for presentation plans: minimizing wait time for a customer and minimizing access bandwidth which, informally speaking, specifies how much network/disk bandwidth is used. We develop algorithms to compute three different optimal presentation plans that work at a block level, or at a segment level, or with a hybrid mix of the two, and compare their performance through simulation experiments. We have also mathematically proven effects of increased buffer or bandwidth and data replications for presentation plans which had previously been verified experimentally in the literature.     

Application-Layer Protocol for Collaborative Multimedia Presentations

Many multimedia presentation applications involve retrieval of objects from more than one collaborating server. Presentations of objects from different collaborating servers might be interdependent. For instance, we can consider distributed video servers where blocks of movies are distributed over a set of servers. Here, blocks of a movie from different video servers have to be retrieved and presented continuously without any gaps in the presentation. Such applications first need an estimate of the available network resources to each of the collaborating server in order to identify a schedule for retrieving the objects composing the presentation. A collaborating server can suggest modifications of the retrieval schedule depending on its load. These modifications can potentially affect the retrieval schedule for other collaborating applications. Hence, a sequence of negotiations have to be carried out with the collaborating servers in order to commit for a retrieval schedule of the objects composing the multimedia presentation. In this paper, we propose an application sub-layer protocol, Resource Lock Commit Protocol (RLCP), for handling the negotiation and commitment of the resources required for a collaborative multimedia presentation application.     

流媒体服务器服务能力基准实验与性能模型

流媒体服务提供商需要了解如何对服务器的服务能力进行测试,如何对系统实时负荷进行估计.本文提出了一组基准实验,测量服务内容为变码率视频时,服务器提供不同质量和方式的视频点播服务的能力,得到与负载相关的服务器性能模型和实时负荷估计方法.实际系统上的验证实验表明,该性能模型可以准确刻画服务器的实时负荷.     

基于磁盘系统的多用户视频准入算法

分析了基于磁盘系统的视频服务器的准入策略,提出了基于磁盘系统的为保证视频服务器接纳更大数目用户的准入算法,即在每个服务周期中每个用户要求检索到的数据块的数目与其对应的回放速率成比例,视频服务器通过过量预约资源来允许更大数量的客户数。这种算法允许视频服务器接纳更大数目的用户,满足多用户媒体回放的稳态性和迁移态连续性的要求。     

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.     

ZipfAllocation: an algorithm for static allocation of movies in a cluster of video servers

When a single video server provides a streaming service, there are many limitations. Thus, clusters of multiple video servers are widely used today to provide better service. How movies are allocated to each server in a cluster is an important and ongoing research topic because the movies are large, and there are so many of them. We have developed a movie allocation algorithm based on the observation that client accesses follow a Zipf distribution. We have developed an algorithm in which servers use their storage to their full capacities, movies are assigned to servers as evenly as possible, servers receive requests as evenly as possible, and all movies are allocated to at least one server. Copyright © 2010 John Wiley & Sons, Ltd.     

CoRAL: A transparent fault-tolerant web service

The Web is increasingly used for critical applications and services. We present a client-transparent mechanism, called CoRAL, that provides high reliability and availability for Web service. CoRAL provides fault tolerance even for requests being processed at the time of server failure. The scheme does not require deterministic servers and can thus handle dynamic content. CoRAL actively replicates the TCP connection state while maintaining logs of HTTP requests and replies. In the event of a primary server failure, active client connections fail over to a spare, where their processing continues seamlessly. We describe key aspects of the design and implementation as well as several performance optimizations. Measurements of system overhead, failover performance, and preliminary validation using fault injection are presented.     

An algorithmic analysis of multi-server vacation model with service interruptions

Motivated by the trade-off between reliability and utilization level of a stochastic service system, we considers a Markovian multi-server vacation queueing system with c unreliable servers. In such a system, some servers may not be available due to either planned stoppage (vacations) or unplanned service interruptions (server failures). The vacations are controlled by a threshold policy. With this policy, at a service completion instant, if d (?c) servers become idle, they take a vacation together and will keep taking vacations until they find at least c − d + 1 customers are in the system at a vacation completion instant, and then they return to serve the queue. In addition, all on-duty servers are subject to failures and can be repaired within a random period of time. We formulate a quasi-birth–death (QBD) process, establish the stability condition, and develop a computational algorithm to obtain the stationary performance measures of the system. Numerical examples are presented to show the performance evaluation and optimization of such a system. The insights gained from this model help practitioners make capacity and operating decisions for this type of waiting line systems.     

Load sharing in distributed multimedia-on-demand systems

Service providers have begun to offer multimedia-on-demand services to residential estates by installing isolated, small-scale multimedia servers at individual estates. Such an arrangement allows the service providers to operate without relying on a highspeed, large-capacity metropolitan area network, which is still not available in many countries. Unfortunately, installing isolated servers can incur very high server costs, as each server requires spare bandwidth to cope with fluctuations in user demand. The authors explore the feasibility of linking up several small multimedia servers to a (limited-capacity) network, and allowing servers with idle retrieval bandwidth to help out servers that are temporarily overloaded; the goal is to minimize the waiting time for service to begin. We identify four characteristics of load sharing in a distributed multimedia system that differentiate it from load balancing in a conventional distributed system. We then introduce a GWQ load sharing algorithm that fits and exploits these characteristics; it puts all servers' pending requests in a global queue, from which a server with idle capacity obtains additional jobs. The performance of the algorithm is captured by an analytical model, which we validate through simulations. Both the analytical and simulation models show that the algorithm vastly reduces wait times at the servers. The analytical model also provides guidelines for capacity planning. Finally, we propose an enhanced GWQ+L algorithm that allows a server to reclaim active local requests that are being serviced remotely. Simulation experiments indicate that the scheduling decisions of GWQ+L are optimal, i.e., it enables the distributed servers to approximate the performance of a large centralized server     

I/O scheduling for digital continuous media

A growing set of applications require access to digital video and audio. In order to provide playback of such continuous media (CM), scheduling strategies for CM data servers (CMS) are necessary. In some domains, particularly defense and industrial process control, the timing requirements of these applications are strict and essential to their correct operation. In this paper we develop a scheduling strategy for multiple access to a CMS such that the timing guarantees are maintained at all times. First, we develop a scheduling strategy for the steady state, i.e., when there are no changes in playback rate or operation. We derive an optimal Batched SCAN (BSCAN) algorithm that requires minimum buffer space to schedule concurrent accesses. The scheduling strategy incorporates two key constraints: (1) data fetches from the storage system are assumed to be in integral multiples of the block size, and (2) playback guarantees are ensured for frame-oriented streams when each frame can span multiple blocks. We discuss modifications to the scheduling strategy to handle compressed data like motion-JPEG and MPEG. Second, we develop techniques to handle dynamic changes brought about by VCR-like operations executed by applications. We define a suite of primitive VCR-like operations that can be executed. We show that an unregulated change in the BSCAN schedule, in response to VCR-like operations, will affect playback guarantees. We develop two general techniques to ensure playback guarantees while responding to VCR-like operations: passive and active accumulation. Using user response time as a metric we show that active accumulation algorithms outperform passive accumulation algorithms. An optimal response-time algorithm in a class of active accumulation strategies is derived. The results presented here are validated by extensive simulation studies.     

SALSA: QoS-aware load balancing for autonomous service brokering

The evolution towards “Software as a Service”, facilitated by various web service technologies, has led to applications composed of a number of service building blocks. These applications are dynamically composed by web service brokers, but rely critically on proper functioning of each of the composing subparts which is not entirely under control of the applications themselves. The problem at hand for the provider of the service is to guarantee non-functional requirements such as service access and performance to each customer. To this end, the service provider typically divides the load of incoming service requests across the available server infrastructure. In this paper we describe an adaptive load balancing strategy called SALSA (Simulated Annealing Load Spreading Algorithm), which is able to guarantee for different customer priorities, such as default and premium customers, that the services are handled in a given time and this without the need to adapt the servers executing the service logic themselves. It will be shown that by using SALSA, web service brokers are able to autonomously meet SLAs, without a priori over-dimensioning resources. This will be done by taking into account a real time view of the requests by measuring the Poisson arrival rates at that moment and selectively drop some requests from default customers. This way the web servers’ load is reduced in order to guarantee the service time for premium customers and provide best effort to default customers. We compared the results of SALSA with weighted round-robin (WRR), nowadays the most used load balancing strategy, and it was shown that the SALSA algorithm requires slightly more processing than WRR but is able to offer guarantees - contrary to WRR - by dynamically adapting its load balancing strategy.     

Increasing multimedia system throughput with consumption-based buffer management

In a multimedia server, multiple media streams are generally serviced in a cyclic fashion. Due to non-uniform playback rates and asynchronous arrivals of queries, there tends to be spare disk bandwidth in each service cycle. In this paper, we study the issue of dynamically using spare disk bandwidth and buffer to maximize the system throughput of a multimedia server. We introduce the concept of minimizing buffer consumption as the criterion to select an appropriate media stream to utilize the spare system resources. Buffer consumption measures not only the amount of buffer but also the amount of time such buffer space is occupied (i.e., the space-time product). Different alternatives to utilizing spare disk bandwidth are examined, including different rate-adjustable retrievals of an already activated stream and prefetching the next waiting stream. For rate-adjustable retrievals, we study buffer consumption-based and remaining-time-based criteria for selecting an active stream to increase retrievals. Simulations are conducted to evaluate and compare different cases. The results show that (1) minimizing buffer consumption is the right criterion for maximizing the system throughput with spare disk bandwidth; (2) in general, prefetching a waiting stream incurs more buffer consumption, and thus is less effective than rate-adjustable retrieval of active streams in maximizing the system throughput; and (3) the advantage of rate-adjustable retrieval over prefetching is especially significant when service cycle time is small.     

基于云平台的高并发WebGIS服务

随着Internet技术的发展,传统的WebGIS服务器在面对大用户群高并发访问时会出现服务延迟甚至拒绝服务的现象.针对该问题,本文提出了一种基于云平台的应对高并发的WebGIS服务器架构.架构使用云平台为WebGIS服务器提供弹性计算和存储资源,并从负载均衡、缓存设计、数据库集群三方面缓解高并发瓶颈.选择开源服务器端软件GeoServer作为WebGIS应用实验部署.实验数据表明使用缓存机制明显降低了WebGIS服务响应时间.与单物理服务器相比,云平台WebGIS服务器集群架构能够有效处理高并发请求,且随着集群规模扩展,云平台WebGIS系统能够获得良好的加速比.     

基于UPnP技术设计的多媒体云服务最佳播放设备智能选取系统

当前,许多媒体服务供应商利用云技术向使用者提供流媒体云服务。云服务虽然提升了流媒体业务按需访问的便捷性,但用户在使用流媒体云服务的同时操作的智能化程度较低。用户在流媒体文件选择、媒体设备选择及服务器连接方面缺乏智能手段。此外,系统不具有媒体流播放的断点支持功能。本文利用即插即用网络通信协议UPnP,设计了一套最佳播放设备的智能选取模型。本模型通过分析比较媒体文件元数据与播放设备元数据,自动选取最佳的播放设备。同时,本模型通过断点信息的保存来实现媒体文件二次播放的连续性。本模型为流媒体云服务的断点播放和播放设备智能优化选取,提供了一种有效的技术模型。     

视频点播服务器的服务质量控制框架

视频点播服务器工作于开放的网络环境中,系统负载难以预测,其运行时资源瓶颈依赖于实时服务类型.基于性能模型和实时负荷估计方法,本文提出视频点播服务器的服务质量控制框架,提供系统负荷监控、准入控制和区分服务等三种服务质量控制.实际系统的验证实验表明,本文的方法可以有效的对系统负荷进行监控,确保系统负荷稳定在服务提供商希望的水平线以下,向不同级别的用户提供不同质量级别的服务.     

Optimal state-free, size-aware dispatching for heterogeneous -type systems

We consider a cluster of heterogeneous servers, modeled as M/G/1 first-come first-serve queues with different processing speeds. A dispatcher that assigns jobs to the servers takes as input only the size of the arriving job and the overall job-size distribution. This general model captures the behavior of a variety of real systems, such as web server clusters. Our goal is to identify assignment strategies that the dispatcher can perform to minimize expected completion time and waiting time. We show that there exist optimal strategies that are deterministic, fixing the server to which jobs of particular sizes are always sent. We prove that the optimal strategy for systems with identical servers assigns a non-overlapping interval range of job sizes to each server. We then prove that when server processing speeds differ, it is necessary to assign each server a distinct set of intervals of job sizes in order to minimize expected waiting or response times.     

基于协作缓存的视频点播系统中调度设计

随着计算机技术和网络技术的不断进步,视频点播服务已经逐渐变成现实,基于协作缓存的视频点播系统是一个分布式结构,中心集群存放影片数据,本地集群缓存数据并提供视频点播服务,具有很好的可扩展性。该文针对VOD系统的协作缓存,提出了静态调度和动态迁移相结合的调度策略,静态调度能够根据影片数据的缓存分布情况,实时调度服务请求,并同时考虑多个VOD服务器的负载动态平衡;动态任务迁移能对服务流分布进行实时分析,并根据服务数据本地化的原则进行服务迁移,进一步提高了协作缓存的命中率。该文阐述了基于协作缓存的视频点播系统的拓扑结构,对静态调度和动态迁移进行了详细设计,并给出了相应的形式化表示。