OnceAS/Q:一个面向QoS的Web应用服务器

网络分布计算环境下应用系统的需求多样化和复杂性的增长,要求位于中间件层次的Web应用服务器(web application server,简称WAS)从原来的"尽力而为"服务模型转变为服务质量(quality of service,简称QoS)保障模型,为具有不同需求的应用分别提供适宜的服务质量保障.目前的WAS系统在此方面仍然比较薄弱.OnceAS/Q是一个面向QoS的WAS系统,它以QoS规约为基础,为不同应用提供不同的QoS保障能力.OnceAS/Q实现了一个应用QoS保障框架,提供了一组QoS服务组件支持具有QoS需求的应用开发和运行.介绍了OnceAS/Q的体系结构和主要组件,详细阐述了两个关键问题,一是QoS规约的定义及其映射,另一个是面向QoS的服务组件和资源的动态重配.OnceAS/Q原型在Ecperf测试基准下,对其QoS保障能力进行了实验.实验数据表明,在较大规模的应用环境下,OnceAS/Q能够提供更好的服务质量,并且开销是可接受的.     

OASSF：一个灵活的Web应用服务器安全框架*

安全框架OASSF是在安全参考模型OASSRM的基础上提出来的一个分层结构的框架,它通过各种可配置的安全策略提供WAS（Web应用服务器）的安全服务,为在WAS中集成和管理不同的安全机制提供了高度的灵活性和扩展性。该框架在中科院软件所自主研制的OnceAS应用服务器中得到了实现。     

一个Web应用服务器的动态集群设施系统——DCIAS

W eb应用服务器(WAS)集群为W eb计算环境下的企业级应用提供高性能、可靠性和可伸缩性的支持,而有效的集群基础设施是WAS集群得以发挥良好作用的关键。DCIAS是一个面向WAS需求的集群支撑系统,它基于标准协议与WAS进行集成,具有良好的可扩展性。DCIAS提供了灵活的集群管理功能,采用对等式管理方式,能够在运行时进行集群成员动态管理,有效维护集群视图的正确性和一致性,满足了WAS集群的灵活、可靠和高效的要求。     

关于Web应用服务器QoS的研究

网络分布计算环境下应用系统的需求多样化和复杂性的增长,要求位于中间件层次的Web应用服务器（简称WAS）从原来的“尽力而为”服务模型转变为服务质量（quality of service,简称QoS）保障模型,为具有不同需求的应用分剐提供适宜的服务质量保障。目前的WAS系统在此方面仍然比较薄弱。本文主要对WAS的QoS进行研究。并提出一些研究方向。     

支持EJB动态分布的组件迁移模型与算法

Web应用服务器是Web计算环境下的新型中间件,为基于组件的分布式Web应用提供了基础运行平台.组件静态分布限制了事务性Web应用在运行期间适应执行环境变化的能力.为了满足Web应用的动态分布需求,Web应用服务器需在底层为组件提供一种动态迁移的能力.如何维持组件迁移前后的一致性是组件迁移中最棘手的问题之一.为解决此问题,定义了组件迁移一致性约束CMC(component migration constrains),并给出了在J2EE(Java 2 platform enterpnse edition)应用服务器中支持EJB(enterprise Java Bean)动态分布的组件迁移模型和SLB Copy,SFB_Copy,EB_Copy 3个迁移算法.分析得出SLB_Copy,SFB_Copy和EB_Copy均满足CMC约束.迁移模型和算法已在自主研制的Web应用服务器WebFrame2.0中实现,并已应用到自适应负载平衡、失效恢复等多个方面.     

CCSAS:一个高效灵活的应用服务器集群通信系统

可靠的集群通信系统为Web应用服务器集群在高负载条件下满足性能需求提供了基础．本文分析了利用集群技术扩展Web应用服务器对于通信的关键需求，提出了一个高效、灵活的集群通信系统，阐述了该系统的结构和设计，介绍了其中若干关键技术和解决办法，包括多播消息的高效传递、协议层次、可配置集群拓扑结构和备份模式等．本文描述的集群通信系统已在自主研发的OnceAS应用服务器中实现．     

一种基于QoS的自适应失效检测算法

自适应失效检测要求失效检测器能够根据实际应用和网络负载变化动态地改变检测的质量。由于互连网络动态多变,缺乏自适应机制的失效检测器难以满足应用对Qo S的需求。检测速度和精度是自适应失效检测器的关键。对现有自适应失效检测算法进行研究、分析,提出一种基于Qo S的失效检测算法。对历史心跳消息间隔时间采用幂律加权计算其均值,并按照指数分布模型计算下一个消息延迟值,实现一种Qo S-AFD自适应失效检测算法。实验及分析表明该算法具有较高的检测速度和准确性。     

一种Web应用服务器中的反射优化技术

Web应用服务器通过使用反射技术,提供了灵活的动态可重配的特性,但是反射存在性能偏低的问题。基于自主研制的OnceAS应用服务器,对其中的反射性能优化问题进行了研究,提出了一个基于自适应缓存的反射框架,以及一个扩展LRU的优化的缓存替换算法。它们能够提高应用服务器的反射效率,并且保持动态可重配和自适应的特性。     

Web应用服务器中Web Service引擎的设计与实现

Web Service为程序之间的交互提供了基础,实现了独立于程序设计语言的一致化编程模型,并以通用的方法进行应用程序集成。分析了Web应用服务器实现Web Service的关键需求,阐述了在应用服务器中基于SOAP的Web Service引擎的设计与实现,介绍了实现Web Service引擎的若干关键技术和解决办法。Web Service引擎已在自主研发的OnceAS应用服务器中实现。     

一种基于性能模型的中间件自配置框架

高动态的计算环境使得QoS(quality of service)保障对于基于组件的分布式系统越来越重要,软件系统需要具备自我调整的能力以适应外部环境的变化.给出一种自适应的中间件配置框架,能够动态感知负载变化,并自动调整系统参数配置以保持用户所要求的服务质量.该框架的核心是一个基于分层排队网络的性能预测模型,用于指导搜索最优的资源配置,使性能需求得到最大的满足.在OnceAS应用服务器上进行原型实现,并以StockOnline应用做实验,比较了在使用和不使用该框架时的性能需求的满足情况.结果显示,在负载增加时,通过自配置框架的调控,应用性能需求的保障程度得到了较大的提升.     

Web应用服务器自适应负载平衡服务

Web应用服务器是为事务性Web应用提供一系列运行时服务的分布式系统.基于中间件的自适应负载平衡服务是为Web应用服务器提供高可信赖性和高伸缩性的一种有效方法,但目前还存在许多不足,如缺乏服务端透明性、负载策略不可替换等,不能满足Web应用服务器特有的需求.分析了Web应用服务器负载平衡服务的关键需要,设计了一种自适应负载平衡服务,阐述了在J2EE应用服务器WebFrame2.0上实现该服务的若干关键技术及其解决办法,包括可热插拔、负载策略可替换、负载反馈与自适应控制、状态迁移以及容错技术等,最后是相关工作介绍及其比较.该负载平衡服务已在Web应用服务器WebFrame2.0中得以实现.     

基于消息延迟预测的自适应失效检测模型

失效检测是实现高可用性的一个关键技术,通常采用超时机制判断进程是否失效的方法实现。然而,由于网络状况的不断变化,缺乏自适应机制的失效检测器难以满足应用对QoS的需求。自适应失效检测要求失效检测器能够根据实际应用和网络负载变化而动态地改变检测的质量。在对现有自适应失效检测算法研究、分析的基础上提出一种基于消息延迟预测的失效检测模型,采用基于历史消息延迟预测下一个消息延迟的方法,实现了一种PA-AFD自适应失效检测算法。实验及分析表明该算法在保证检测准确性和完整性的同时缓解了网络延迟对失效检测的影响。     

An extensible and lightweight architecture for adaptive server applications

Server applications augmented with behavioral adaptation logic can react to environmental changes, creating self‐managing server applications with improved quality of service at runtime. However, developing adaptive server applications is challenging due to the complexity of the underlying server technologies and highly dynamic application environments. This paper presents an architecture framework, the Adaptive Server Framework (ASF), to facilitate the development of adaptive behavior for legacy server applications. ASF provides a clear separation between the implementation of adaptive behavior and the business logic of the server application. This means a server application can be extended with programmable adaptive features through the definition and implementation of control components defined in ASF. Furthermore, ASF is a lightweight architecture in that it incurs low CPU overhead and memory usage. We demonstrate the effectiveness of ASF through a case study, in which a server application dynamically determines the resolution and quality to scale an image based on the load of the server and network connection speed. The experimental evaluation demonstrates the performance gains possible by adaptive behavior and the low overhead introduced by ASF. Copyright © 2007 John Wiley & Sons, Ltd.     

Web++ architecture,design and performance

We describe the design of a system for fast and reliable HTTP service which we call Web++. Web++ achieves high reliability by dynamically replicating web data among multiple web servers. Web++ selects the available server that is expected to provide the fastest response time. Furthermore, Web++ guarantees data delivery given that at least one server containing the requested data is available. After detecting a server failure, Web++ client requests are satisfied transparently to the user by another server. Furthermore, the Web++ architecture is flexible enough for implementing additional performance optimizations. We describe implementation of one such optimization, batch resource transmission, whereby all resources embedded in an HTML page that are not cached by the client are sent to the client in a single response. Web++ is built on top of the standard HTTP protocol and does not require any changes either in existing web browsers or the installation of any software on the client side. In particular, Web++ clients are dynamically downloaded to web browsers as signed Java applets. We implemented a Web++ prototype; performance experiments indicate that the Web++ system with 3 servers improves the response time perceived by clients on average by 36.6%, and in many cases by as much as 59%, when compared with the current web performance. In addition, we show that batch resource transmission can improve the response time on average by 39% for clients with fast network connections and 21% for the clients with 56 Kb modem connections. This revised version was published online in August 2006 with corrections to the Cover Date.     

一种基于在线辨识的Web 服务自适应接纳控制

设计并实现了一种基于量子行为粒子群算法(QPSO)系统模型在线辨识的Web服务自适应接纳控制,根据系统模型的变化在线调节比例积分控制器参数.通过接纳时间比反馈控制机制,调整控制周期内服务器接纳请求的时间长度,进而实现接纳控制.通过仿真实验,并与多种不同控制方法进行比较,所得结果表明,在线辨识自适应控制能够在服务器过载的情况下更有效地控制系统资源,进一步提高了服务质量.     

Web应用服务器的可扩展管理模型及其实现

Web应用服务器是为事务性Web应用提供一系列运行时服务的分布式系统。它既要管理多种不同类型的资源，又要集成以往成熟的网络管理协议和系统，因此，如何统一有效地管理Web应用服务器的资源、应用和服务成为实现Web应用服务的一个难点。为此，本文基于JMX(Java^TM Management Extensions)技术，提出了一种可扩展管理模型，该模型具有较好的灵活性和开放性，可扩展能力强。同时．本文还给出了实现该模型的若干关键技术包括可扩展管理内核的实现技术、资源远程管理技术、服务可扩展管理技术。目前该模型已在我们研制的Web应用服务器WebFrame2．0中成功实现。     

Models@ Run.time to Support Dynamic Adaptation

Today's society increasingly depends on software systems deployed in large companies, banks, airports, and so on. These systems must be available 24/7 and continuously adapt to varying environmental conditions and requirements. Such dynamically adaptive systems exhibit degrees of variability that depend on user needs and runtime fluctuations in their contexts. The paper presents an approach for specifying and executing dynamically adaptive software systems that combines model-driven and aspect-oriented techniques to help engineers tame the complexity of such systems while offering a high degree of automation and validation.     

Composing Web Services: A QoS View

An Internet application can invoke several services--a stock-trading Web service, for example, could invoke a payment service, which could then invoke an authentication service. Such a scenario is called a composite Web service, and it can be specified statically or established dynamically. Dynamic composition of Web services requires service consumers to discover service providers that satisfy given functional and nonfunctional requirements including cost and QoS requirements such as performance and availability. In previous columns, I've examined how quality of service (QoS) comes into play for service providers, consumers, and parallel transactions. Here, I'll show how it fits into composite Web services.     

An adaptive QoS-aware fault tolerance strategy for web services

Service-Oriented Architecture (SOA) is widely adopted for building mission-critical systems, ranging from on-line stores to complex airline management systems. How to build reliable SOA systems becomes a big challenge due to the compositional nature of Web services. This paper proposes an adaptive QoS-aware fault tolerance strategy for Web services. Based on a user-collaborated QoS-aware middleware, SOA systems can dynamically adjust their optimal fault tolerance configurations to achieve optimal service reliability as well as good overall performance. Both the subjective user requirements and the objective system performance of the Web services are considered in our adaptive fault tolerance strategy. Experiments are conducted to illustrate the advantages of the proposed adaptive fault tolerance strategy. Performance and effectiveness comparisons of the proposed adaptive fault tolerance strategy and various traditional fault tolerance strategies are also provided.     

Comparison of fault detection and isolation methods for a small unmanned aircraft

This paper compares three model-based methods for detecting and isolating stuck control surface faults on a small unmanned aircraft. The first method is parity-space based and compares a sensor measurement against a model-based prediction of the same quantity. The second method is observer-based and involves robust estimation for linear parameter-varying systems. The third method is also observer-based and involves multiple model adaptive estimation. The performance of the three methods are compared using flight data. The comparison shows that the three methods have different detection performance and runtime. The selection of a particular method depends on the application requirements and implementation constraints.