排队论在高校选课系统服务台模型设计中的应用

在高校网络系统中,随着客户机数量和密集性任务的增加,单个Web服务器受到处理能力的限制,已经成为网络访问的新瓶颈。若增加Web服务器缓解资源的紧张,则可能造成成本增加,设备闲置。因此,Web服务器具备高可用性将成为解决这一问题的最佳方法。在综合考虑选课系统中主要应用的算法基础上,以概率动态分布为基础,综合运筹学中的排队论原理,建立一种应用在高校选课系统中的多通道等待服务台模型。实践结果证明,文中提出的模型应用在高校选课系统中,减少运营成本,提高服务水平效果。     

分配器上支持QoS的设计与实现

为了让Web集群服务器支持QoS，在分配器上实现了一些QoS的机制，包括区分服务、性能隔离、服务器动态划分、接纳控制和内容自适应。对于高优先级的请求，系统确保其服务质量满足事先商定的服务质量协议；对于低优先级的请求，系统提供尽力而为的服务。尤其，当服务器重载时，分配器不是简单地靠丢弃请求，而是采用内容自适应机制来防止服务器过载。实际测试表明，系统达到了所有的设计要求。     

Web服务器群的QoS确保及其接纳控制研究

WWW访问的爆炸性发展正是Internet成功的重要原因，然而目前的Web服务器却缺乏相应的QoS机制，导致在过载时造成巨大的经济损失。一个提供多类服务的多服务器Web平台的服务质量确保体系被提出来，它以服务响应延迟为核心度量标准，将同一类服务抽象为一台虚拟服务器，并以该度量黏合起系统的各个组件．同时据此提出了一个动态自适应的服务接纳算法(DASAC)．测试表明，即使经历严重的过载与业务突发，也能保证用户感知的服务质量．     

Web服务器中基于自适应控制的成比例延迟区分服务

Internet上Web应用日益广泛的使用,使得Web服务器需要在高负载下提供性能保证与区分服务,以满足用户的不同需求。响应延迟是评价Web服务器的一项关键性能指标,而成比例延迟区分服务是一种重要的区分服务模型。针对Apache Web服务器,提出并实现了基于自适应控制的成比例延迟区分服务。在每个采样周期,自适应控制器根据预设的延迟区分参数,通过动态计算并调节各个客户类别的服务线程数目,可保证Apache Web服务器上高优先级客户具有较低的平均连接延迟,而各个客户类别的平均延迟比保持不变。仿真结果表明,在动态变化的负载、参考输入以及不同的系统配置之下,控制器作用下的Apache Web服务器都能可靠地提供成比例延迟区分服务。     

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     

Connection management for QoS service on the Web

The current Web service model treats all requests equivalently, both while being processed by servers and while being transmitted over the network. For some uses, such as multiple priority schemes, different levels of service are desirable. We propose application-level TCP connection management mechanisms for Web servers to provide two different levels of Web service, high and low service, by setting different time-outs for inactive TCP connections. We evaluated the performance of the mechanism under heavy and light loading conditions on the Web server. Our experiments show that, though heavy traffic saturates the network, high level class performance is improved by as much as 25–28%. Therefore, this mechanism can effectively provide QoS guaranteed services even in the absence of operating system and network support.     

Multiclass Multiserver Threshold-Based Systems: A Study of Noninstantaneous Server Activation

In this paper, we consider performance evaluation of a system which shares K servers (or resources) among N heterogeneous classes of workloads, where server allocation and deallocation for class i is dictated by a class specific threshold-based policy with hysteresis control. In particular, the server activation time for class i is noninstantaneous. There are many systems and applications where a multiclass threshold-based queueing system can be of great use. One important utility of using threshold-based approaches is in situations where applications may incur server usage costs. In these cases, one needs to consider not only the performance aspects but also the resulting cost/performance ratio. The motivation for using hysteresis control is to reduce the unnecessary cost of server setup (or activation) and server removal (or deactivation) whenever there are momentary fluctuations in workload. Moreover, servers in such systems and applications are often needed by multiple classes of workloads and, hence, it is desirable to find good approaches to sharing server resources among the different classes of workloads, preferably without statically partitioning the server pool among these classes. An important and distinguishing characteristic of our work is that we consider the modeling and analysis of a multiclass system with noninstantaneous server activation. The main contributions of this work are: 1) in developing an efficient approximation method for solving such models; 2) in verifying the convergence of our iterative method, and 3) in evaluating the resulting accuracy of the technique for computing performance measures of interest, which can subsequently be used in making system design choices     

WC-Stress:基于QoS的Web集群服务器性能评价工具

针对当前Web通用服务器性能评测工具并不能满足Web集群系统性能评测的需要,该文的研发重点在于构造一个高性能的支持QoS的Web集群服务器评测工具WC-Stress(WebClusterStress)。它的特点包括:可组装的组件结构;支持Web集群的评测需要:如区分服务;支持细粒度的QoS性能评测:如资源优化调度算法的支持;支持新的Web访问特征:如自相似请求的产生。最后给出了此评测工具对笔者设计的一种新型Web集群服务器的测试结果。     

SDFS: A software-defined file system for multitenant cloud storage

Performance isolation is highly desirable in cloud platforms where the virtual disks of virtual machines are simply large files on the shared and networked storage servers. However, existing isolation techniques cannot deal with the implications of the file system used by the networked storage servers, such that underlying resource usage is unpredictable (eg, the delayed write-back mechanism could postpone writes, and the journaling mechanism could amplify writes). The lack of visibility on underlying resource usage leads to the predicament of being unable to meet isolation goals. In this paper, we present a software-defined file system (SDFS) that exploits the underlying file system to allocate resources at per-image-file granularity and provide tenants with guaranteed throughput. The SDFS comprises two components: control plane and data plane. At the control plane, we provide a set of system calls to document tenant performance requirements into the metadata of image files. At the data plane, we construct a file-based scheduler to manage memory and disk resources according to the tenant performance requirements. The SDFS design does not require a modification to guest operating systems, hypervisors, or file server protocols. Through a prototype implementation, we demonstrate that the SDFS can meet isolation goals and increase resource utilization with negligible overhead.     

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     

共享式Web应用服务器集群的资源整合方法研究

PaaS(platform as a service)平台是一种重要的云计算服务类型,但传统的Web应用服务器集群管理方式无法为PaaS平台多承租和动态资源管理提供有效支持。针对上述问题,提出了一种基于进程隔离的共享式集群拓扑结构,支持多个Web应用服务器集群共享相同的物理服务器环境。同时给出了针对此共享集群的服务器整合方法,以满足租户应用的性能需求和提高服务器的有效资源使用率。实验证明,平台能够根据当前共享集群的状态选择适当数量的服务器,服务器整合方法有效可行。     

异构Web集群中的比例伸展因子区分服务

Web集群服务器已被广泛用来提高Web服务器的性能。如何保证Web服务的服务质量（QoS）是一个迫切需要解决的问题。区分服务已成为QoS研究领域中的一个焦点。本文分析了Web请求服务时间的数字特性,并使用M／G／1 FCFS排队模型对Web服务器及Web集群服务器进行了建模。在对模型进行分析的基础上,设计并实现了一种异构Web集群服务器中的比例伸展因子区分服务的方案,并提出了基于概率空间的请求调度算法。请求被分成多个类,无论系统的负载如何,系统确保每类请求的平均伸展因子与事先给定的参数成正比。实际测试表明,所设计的方案满足相对区分服务的可预测性和可控制性的要求。     

SMPED：一种新型高性能服务器体系结构

分析了几种服务器软件体系结构存在的优点与缺陷，设计了一种结合多进程并发与单进程事件驱动优点的对称式多进程事件驱动SMPED服务器体系结构。提出了一种新颖的连接调度算法，该算法根据服务器实际吞吐量进行连接分发和资源分配，试图实现服务器吞吐量最大化。仿真试验证明，SMPED服务器性能在多种网络条件下明显优于现行服务器。     

A two-class parallel system with general service times of the parallel class

A parallel system with two job classes is analyzed. Type-1 jobs require one server for their execution and have exponentially distributed service times while type-2 jobs need two servers and have general service times. The model consists of a single queue served by two servers that may work either independently or in parallel. It is assumed that all jobs are rigid and share the servers according to pure space sharing. We provide closed-form expressions, exact as well as approximate, for various performance measures of interest. The approximate formula is found to be extremely accurate for various distributions of the service times of type-2 jobs. Furthermore, the maximal occupancy of the servers as well as the maximal throughput are examined. Finally, numerical results to investigate the impact of each parameter on system performance are conducted.     

基于AHP的Web集群系统负载均衡算法

利用集群技术构建的服务器组在资源利用率上存在较大差异。为此,提出基于层次分析法(AHP)的集群系统负载均衡算法,建立判断矩阵,得到各项评估指标的单项和综合权重。调度器定时接收真实服务器上的4类参数：网络性能,服务器硬件,服务器软件和网络服务类型。根据调度器收到的每一个连接请求,采用动态反馈算法选择负载最小的服务器响应连接请求。实验结果表明,该算法能减少服务器平均响应时间,有效提高集群系统的响应率。     

网络控制系统Web服务器服务质量管理方案的研究

提出一种基于Web的自适应内容传输管理方案,为不同网络客户提供不同优先级的性能服务,并且各种服务相互独立,同时能基于请求率和传输带宽共享系统资源。这种方案在传统的允入控制基础上改善了服务性能,根据网络负载情况和服务质量需求自适应选择传输内容,满足了客户对网络传输服务质量需求。该管理方案可以在三层模型的中间层实施,便于修改和维护,给出的实验结果显示了该方案的有效性。     

Web 服务器的鲁棒建模和过载控制

给出了一种Web 服务器的建模方法,说明了如何用控制理论管理不可预测的服务器负载。Web 服务器可以被仿真为一个多容器系统。该鲁棒Web 服务器模型适用于未知的负载干扰和不确定的匹配模型。过载控制技术基于自适应允许控制取得时间保证,用一个完整参数变化模型和大的过载来评估模型的性能。     

基于标记的缓存协作分布式Web服务器系统

介绍了提高Web服务器性能的前沿技术--分布式Web服务器系统,讨论了现有各种方案的优缺点,在此基础上提出一种新的分布式Web服务器系统.该系统使用基于标记的缓存协作用户请求分发方法(tag based cache cooperative Web requests distribution,简称TB-CCRD),通过前端机把系统中各个Web服务器的缓存组织成一个大的虚拟缓存系统,提高系统的整体缓存命中率,缩短了请求的响应时间;通过分布式处理TCP连接转交来消除前端机的性能瓶颈;利用标记通告URL在缓存中的位置,避免了额外的系统内部通信.从而得到了一个可扩展的高性能分布式Web服务器系统.     

基于防火墙的内网信息发布探讨

本文主要是探讨对Windows XP系统中自身内置的防火墙ICF1服务功能进行设置,把架设在内网计算机中的Web服务器、FTP服务器、Telnet服务器、邮件服务器等网络服务信息发布到互联网中,让更多的人通过互联网随时随地分享架设在内网中的资源,实现资源共享。     

A predictive and probabilistic load-balancing algorithm for cluster-based web servers

The exponential demands for high performance web servers led to use of cluster-based web servers. This increasing trend continues as dynamic contents are changing traditional web environments. Increasing utilization of cluster web servers through effective and fair load balancing is a crucial task specifically when it comes to advent of dynamic contents and database-driven applications on the internet. The proposed load-balancing algorithm classifies requests into different classes. The algorithm dynamically selects a request from a class and assigns the request to a server. For both the scheduling and dispatching, new probabilistic algorithms are proposed. To avoid using unreliable measured utilization in the face of fluctuating loads the proposed load-balancing algorithm benefits from a queuing model to predict the utilization of each server. We also used a control loop feedback to adjust the predicted values periodically based on soft computing techniques. The implementation results, using standard benchmarks confirms the effectiveness of proposed load-balancing algorithm. The algorithm significantly improves both the throughput and mean response time in contrast to two existing load-balancing algorithms.