自主计算软件工程方法

从软件工程角度对自主计算进行研究，定义了一种自、主计算系统模型．以此模型为基础，提出了一种多主体系统设计方法DPMAS用于自主计算系统的建模，提出了一种基于构件复用的层次化自主计算未统开发方法．根据研究成果，实现了一个自主计算开发环境，较好的支撑了自主计算系统的软件工程过程．     

"旅游一卡通"系统的研究与设计

通过分析河南旅游的特点,对"旅游一卡通"系统进行了研究与设计.文章阐述了"旅游一卡通"的功能,并对系统的总体设计进行了研究.分析了传统三层应用软件系统的不足,提出了一个适合该系统运行的新的四层体系结构.文章的最后提出了一个"旅游一卡通"计费系统模型.该模型利用了目前国内比较热门的业务规则管理技术,使计费规则与程序代码完全分开,便于计费规则的灵活运用.     

自主计算环境

自主计算技术是为了解决软件复杂性危机而提出的一门新兴的研究课题。该文分析了目前自主计算研究的现状和不足，提出了一种自主计算系统的建模方法，给出了自主单元和自主计算系统体系结构，并在该结构的基础上实现了自主计算环境ACE。     

基于状态的通用自主计算模型

针对目前由于计算系统庞大造成管理工作复杂以及处理突发事件低效的问题,提出一种通用的自主计算模型.通过归纳系统的运行状态和状态变化,利用统计记分方法对状态变化进行判定和标记,实现了包含自我配置、恢复、优化和保护在内的自主计算特性,使系统可以自主地规划最能够满足系统运行需求的方案,从而将繁重的系统配置和突发事件处理任务由管理人员移交给系统自身.实验结果表明,该运用该模型能够在减轻管理负担的情况下,自主地实现系统资源的合理配置与使用.     

基于普适环境的自适应系统研究

作为新的计算模式,普适计算为应用技术界开辟了一个崭新、宽阔的研究领域.普适计算的目标是无时无处不在而又不可见,具有泛在性、便捷性和适应性的特点,对软件自适应机制提出了新的挑战.针对自适应技术用于普适计算下存在的问题,对自适应技术的体系结构展开研究,提出了一个适用于普适计算环境的自适应中间件模型.力图实现一种能够较好支持普适计算环境的软件基础架构,并通过分布仿真原型系统的实验比较说明该中间件体系结构的执行效率.对自适应系统与自适应策略进行了探讨.     

计算物理系统网络拓扑模型研究

计算物理系统是一个典型复杂系统,网络化是计算物理系统区别于以往智能系统的一个重要特性,构建网络拓扑模型成为研究计算物理系统的基础性问题.分析计算物理系统的工作信息流程以及系统网络化结构基础上,提出了感知、计算和控制3类功能节点模型,构建了以矩阵形式和立体形式表示的计算物理系统3重立体网络拓扑模型.智能交通案例表明,该模型能够清晰地描述计算物理系统的网络拓扑,为计算物理系统网络特性的分析提供基础,有利于计算物理系统抗毁性等特性以及演化规律的研究.     

一个基于服务的网格计算模型

文中提出一个基于服务的网格计算模型,该模型强调了一个网格就是一个特殊的计算系统。通过这个模型与传统计算系统模型的比较,分析了它们的相似点和不同点,这对于网格的研究是很重要的。文中所提出的模型对网格计算的研究也是非常有用的。它不仅为开发一个网格系统提供了一定的帮助,而且为网格理论上的研究提供了一个框架。     

基于"嵩山"超级计算机系统的量子傅里叶变换模拟

"嵩山"超级计算机系统是中国自主研发的新一代异构超级计算机集群,其搭载的CPU和DCU加速器均为我国自主研发.为扩充该平台的科学计算生态,验证量子计算研究在该平台上开展的可行性,文中使用异构编程模型实现了量子傅里叶变换模拟在"嵩山"超级计算机系统上的异构版本,将程序的计算热点部分分配至DCU上运行;然后使用MPI在单计算节点上开启多进程,实现DCU加速器数据传输和计算的并发;最后,通过计算与通信的隐藏避免了DCU在数据传输时处于较长时间的空闲状态.实验首次在超算系统上实现了44 Qubits规模的量子傅里叶变换模拟,结果显示,异构版本的量子傅里叶变换模拟充分利用了DCU加速器计算资源,相较于传统CPU版本,其取得了11.594的加速比,且在集群上具有良好的可拓展性,该方法为其他量子算法在"嵩山"超级计算机系统上的模拟实现以及优化提供了参考.     

无人系统自主等级模糊评价方法

为了评价无人系统在处理任务时的自主等级,本文构造了一个自主等级评定模型.它首先对系统执行行为序列后产生的反馈值进行分析,建立了一套评价自主等级的指标体系,包括环境的变化量、任务的完成度、系统状态的稳定度以及操作者和系统的交互程度.然后.将模糊集合论的思想和方法引入其中,提出模糊决策的方法来计算出无人系统的自主等级.最后,给出一个实例并进行验证.     

一个基于服务的网格计算模型

文中提出一个基于服务的网格计算模型，该模型强调了一个网格就是一个特殊的计算系统。通过这个模型与传统计算系统模型的比较，分析了它们的相似点和不同点，这对于网格的研究是很重要的。文中所提出的模型对网格计算的研究也是非常有用的。它不仅为开发一个网格系统提供了一定的帮助，而且为网格理论上的研究提供了一个框架。     

Agents and Service-Oriented Computing for Autonomic Computing: A Research Agenda

Autonomic computing is the solution proposed to cope with the complexity of today's computing environments. Self-management, an important element of autonomic computing, is also characteristic of single and multiagent systems, as well as systems based on service-oriented architectures. Combining these technologies can be profitable for all — in particular, for the development of autonomic computing systems.     

自主系统中的一种优化模型设计

自优化是自主计算系统的一个基本能力,而性能函数为实现自主计算系统的这种能力提供了一个自然且基本的框架。自主元素是自主计算系统的基本建设模块,而被管理组件是自主元素的管理对象。文中将被管理组件划分为资源和服务,然后给出了性能函数的模型,从而提供了自优化的目标。最后,讨论了在自主元素环境下的自优化过程。     

Ontological Semantics for Distributing Contextual Knowledge in Highly Distributed Autonomic Systems

Much recent research has focused on applying Autonomic Computing principles to achieve constrained self-management in adaptive systems, through self-monitoring and analysis, strategy planning, and self adjustment. However, in a highly distributed system, just monitoring current operation and context is a complex and largely unsolved problem domain. This difficulty is particularly evident in the areas of network management, pervasive computing, and autonomic communications. This paper presents a model for the filtered dissemination of semantically enriched knowledge over a large loosely coupled network of distributed heterogeneous autonomic agents, removing the need to bind explicitly to all of the potential sources of that knowledge. This paper presents an implementation of such a knowledge delivery service, which enables the efficient routing of distributed heterogeneous knowledge to, and only to, nodes that have expressed an interest in that knowledge. This gathered knowledge can then be used as the operational or context information needed to analyze to the system's behavior as part of an autonomic control loop. As a case study this paper focuses on contextual knowledge distribution for autonomic network management. A comparative evaluation of the performance of the knowledge delivery service is also provided. John Keeney holds a BAI degree in Computer Engineering and a PhD in Computer Science from Trinity College Dublin. His primary interests are in controlling autonomic adaptable systems, particularly when those systems are distributed. David Lewis graduated in Electronics Engineering from the University of Southampton and gained his PhD in Computer Science from University College London. His areas of interest include integrated network and service management, distributed system engineering, adaptive and autonomic systems, semantic services and pervasive computing. Declan O’Sullivan was awarded his primary degree, MSc and PhD in Computer Science from Trinity College Dublin. He has a particular interest in the issues of semantic interoperability and heterogeneous information querying within a range of areas, primarily network and service management, autonomic management, and pervasive computing.     

凌云体系结构及关键技术研究

云计算系统的基本模型、体系结构、关键技术与系统实现是当前学术界、IT企业界共同关注的热点问题.通过分析现存的2种云计算系统特征,包括垂直型和混合型云计算系统,发现构建生产性云计算系统过程中的3个重要且富有挑战性的问题:异构应用负载模式的高效支持、多租户的资源租赁和利用一套统一的系统整合海量异构的云资源.针对这些问题,简单介绍了凌云系统的组成与目标,提出了一种基于资产租约模型的云计算系统体系结构,并对资产分区管理、虚拟网络管理、虚拟电器管理、虚拟机群租赁框架、全局云用户管理等关键技术进行了简要分析.目前,凌云系统已经实现,并且已在实际环境中部署和实施.根据评价结果,凌云在统一性、灵活性、安全性、好用性和高效性等非功能性目标上基本都优于另外2套系统:OpenNebula和EnomalyECP.性能测试数据表明,在64个虚拟机同时部署的情况下,凌云的虚拟机平均逻辑部署速度能够达到OpenNebula和VIDA组合的4.1倍.     

Concurrency of self-* in autonomic systems

New computing systems are currently at crucial point in their evolution: autonomic systems (ASs), which are inspired by the human autonomic nervous system. Autonomic computing (AC) is characterized by self-*such as self-configuration, self-healing, self-optimization, self-protection and more which run simultaneously in ASs. Hence, self-*is a form of concurrent processing in ASs. Taking advantage of categorical structures we establish, in this paper, a firm formal basis for specifying concurrency of self-* in ASs.     

一种关键任务系统自律可信性模型与量化分析

将现有入侵容忍、自毁技术与自律计算相结合,提出了一种基于SM-PEPA(semi-Markov performance evaluation process algebra)的关键任务系统自律可信性模型以支持形式化分析和推理.该模型具有一定程度的自管理能力,采用分级处理的方式应对各种程度的可信性威胁,满足了关键任务系统对可信性的特殊需求.在此基础上,从稳态概率角度提出了一种自律可信性度量方法.最后,结合具体实例对模型参数对自律可信性的影响进行了初步分析.实验结果表明,增大关键任务系统可信性威胁检测率和自恢复成功率,可在较大范围内提高系统的自律可信 特性.     

Toward Open-World Software: Issue and Challenges

Traditional software development is based on the closed-world assumption that the boundary between system and environment is known and unchanging. However, this assumption no longer works within today's unpredictable open-world settings, especially in ubiquitous and pervasive computing settings, which demand techniques that let software react to changes by self-organizing its structure and self-adapting its behavior. The more we move toward dynamic and heterogeneous systems, and the more we stress their self-healing and self-adapting capabilities, the more we need new approaches to develop these applications and new ways to structure and program them. Programming open systems requires new programming language features. Two features that bear investigation are introspection mechanisms to get runtime information about newly encountered services and reflective mechanisms to adapt client applications dynamically. Some existing standards, industrial products, and research prototypes that support, to a certain extent, the open-world assumptions are service-oriented technologies, publish/subscribe middleware systems, grid infrastructures, autonomic frameworks     

Adaptive atomic capture of multiple molecules

Facing the scale, heterogeneity and dynamics of the global computing platform emerging on top of the Internet, autonomic computing has been raised recently as one of the top challenges of computer science research. Such a paradigm calls for alternative programming abstractions, able to express autonomic behaviours. In this quest, nature-inspired analogies regained a lot of interest. More specifically, the chemical programming paradigm, which envisions a program’s execution as a succession of reactions between molecules representing data to produce a result, has been shown to provide some adequate abstractions for the high-level specification of autonomic systems.