一个网格经济学模型和信用机制

网格的目标是实现对地理上广泛分布的大量异构资源进行共享.然而,由于网格具有的异构性、分布性和动态性,网格环境中的资源管理是个复杂的问题.将经济学原理,例如一些经济学模型和市场机制引入网格之中构建网格经济学资源管理模型,能够很好地配合网格的离散特性.该文将经济学原理引入网格环境之中,提出了一个“信用机制”,使用户能够根据服务提供者的“信用”来优化选择,同时使网格更为高效和有序.     

网格计算环境下资源管理的研究

网格计算是下一代互联网的应用模式,资源管理是网格技术研究的核心任务之一,包含资源发现、任务调度和负载均衡.由于网格中的资源具有分布性、自治性、异构性和动态性,对网格资源进行高效的管理是一个具有挑战性的问题.通过对各种资源管理模型的对比,提出把移动Agent和计算经济机制引入网格资源管理,可以很好地进行资源的发布、资源发现和资源的调度.     

网格工作流技术综述

网格资源的多样性、动态性、异构性、分布性,使得网格任务的处理限制,网格工作流能有效对网格应用进行调度、管理监控。从而提高了网格环境下的工作效率。本文在探讨网格工作流特点的基础上,详细地分析了网格工作流的发展,并对网格工作流的体系结构和功能进行了分析,其后进一步讨论了几种典型的网格工作流系统,最后对网格工作流技术的不足之处进行了分析总结。     

一种基于蚁群算法的网格任务调度方法

网格资源具有动态变化,广域分布及系统异构的特性,如何分配调度这些资源成为网格计算研究领域一个重要研究课题。国内外在网格任务调度研究上已经做了大量工作,但是这些算法大多是基于计算网格的,不能很好的适应服务网格环境下存在任务相关性的调度,同时在适应网格的动态性、异构性上也存在不足。针对目前网格调度机制存在的问题,提出了一种基于蚁群算法的服务网格任务动态调度方法,仿真实验结果表明该算法具有较好的性能和自适应性。     

动态自适应性网格资源管理模型研究

由于网格计算中的资源具有分布性、自治性、异构性和动态性，对计算网格资源进行高效的管理是一个具有挑战性的问题。提出了把移动代理技术引入网格计算资源管理，从而为资源管理提供一个自适应性的广域资源环境，使网格计算系统能够自动适应环境的变化，为网格计算资源管理的动态自适应性研究指引了方向。     

面向服务的学习资源网格及其演示系统设计与实现

随着研究的发展,网格技术由计算为中心演变为以服务为中心。文章以学习资源为研究对象构建学习资源网格,将性能各异的学习资源抽象设计为网格服务,屏蔽底层资源的异构性。在此基础上对学习资源网格进行了模拟演示,将抽象的网格技术可视化,形象地展示学习资源网格的工作原理、特点及服务调用流程,使网格研究者和用户对学习资源网格有更清晰直观地理解和认识。     

网格计算在图书文献信息检索中的应用

本文首先介绍了基于元数据表示的信息网格相关技术,探讨了信息网格技术在图书文献信息资源中的应用.论文从整合分布异构信息资源入手,以现有主流网格中间件Globus Toolkit为基础研究平台,基于目前图书文献信息数据库分布零散,内部实现存在异构性,难以满足跨库统一检索的实际需求,提出了一种基于信息网格层的异构跨库信息服务体系结构和基于元数据的资源整合技术,并从信息网格总体结构和逻辑结构进行了分析与设计,最后并详细实现了MDS信息服务组件.     

一种基于最小代价的网格资源发现模型

引入域和资源路由节点的概念,设置最小代价函数对网格资源进行分层按域划分,形成一种基于最小代价的分层次网格资源发现模型;并为模型设计了相应的资源路由器节点选择算法、资源注册和查询算法。性能分析和模拟实验结果表明,模型具有良好的可扩展性和容错性,且系统代价低;模型能够在屏蔽网格资源异构性的同时很好地满足其动态性、分布性和扩展性的要求,具有较高的资源搜索性能。     

基于博弈理论的网格资源共享协同算法

针对网格资源共享的自治性、异构性、分布性和并行性,在考虑网格资源管理及结点行为特点的基础上,建立了网格资源竞价博弈模型,进而提出了一种基于博弈论的资源共享的协同算法,仿真实验结果表明该算法实现了资源供需变化的自适应以及使用效益意义上的资源负载平衡。     

基于Agent的网格资源分层管理模型设计

资源管理系统是网格最核心的组成部分。网格上的资源具有分布性、异构性、动态性等特点。使得网格中资源共享的实现比以前的系统更加困难，资源管理系统设计的难度也相应增加了。目前。国内外对网格资源管理的相关研究主要包括理论模型和实验产品两个方面。这两方面的研究都做得还不够，现有的产品还不够成熟。本文提出了一种基于Agent的资源分层管理模型，对各层功能进行了详细说明。     

网格资源的超拓扑空间模型

为了更好地共享和使用网格资源,资源模型已经成为网格计算的重要研究问题之一。论文从超拓扑空间的角度重新审视了网格资源模型的内在机理与结构,对资源的描述、抽象以及单一系统映像方法进行了深入的研究,提出了一个形式化资源模型,具有三层结构,分别是:特征信息层、特征处理层和功能层。各层有着不同的组织形式与拓扑结构,并且进一步可细分为若干亚层;利用所提出的聚类方法,上层结构可由下层自动形成。应用分析表明,该模型能够有效地提高网格资源管理系统的可用性、模块性、透明性和自动化。     

A Market-Oriented Grid Directory Service for Publication and Discovery of Grid Service Providers and their Services

The emergence of Grids as a platform for sharing and aggregation of distributed resources increases the need for mechanisms that allow an efficient management of resources. The Grid economy has been identified as one of the potential solutions as it helps in managing the supply and demand for resources and enables sustained sharing of resources by providing economic incentive for Grid resource providers. An economy based Grid computing environment needs to support an infrastructure that enables the creation of a marketplace for meeting of providers and consumers. This paper presents the Grid Market Directory (GMD) that serves as a registry for publication and discovery of Grid service providers and their services.     

A computational economy for grid computing and its implementation in the Nimrod-G resource broker

Computational grids that couple geographically distributed resources such as PCs, workstations, clusters, and scientific instruments, have emerged as a next generation computing platform for solving large-scale problems in science, engineering, and commerce. However, application development, resource management, and scheduling in these environments continue to be a complex undertaking. In this article, we discuss our efforts in developing a resource management system for scheduling computations on resources distributed across the world with varying quality of service (QoS). Our service-oriented grid computing system called Nimrod-G manages all operations associated with remote execution including resource discovery, trading, scheduling based on economic principles and a user-defined QoS requirement. The Nimrod-G resource broker is implemented by leveraging existing technologies such as Globus, and provides new services that are essential for constructing industrial-strength grids. We present the results of experiments using the Nimrod-G resource broker for scheduling parametric computations on the World Wide Grid (WWG) resources that span five continents.     

基于经济模型的资源代理

网格计算是为解决大规模资源密集型问题而提出的新一代计算平台,是当前并行和分布处理技术的一个发展方向,而资源管理是计算网格的关键技术之一。对各种各样可利用资源的整合和管理是网格应用的基础,而资源的分布性、动态性、异构性、自治性和需要协调一致性使得网格资源的管理调度成为一个棘手的问题。目前基于市场的经济资源管理和调度算法非常适合计算网格中的资源管理问题,但有调度价格不能更改、负载平衡等问题。文中提出了“网格环境下基于经济模型的资源代理”,依靠多维QoS指导的调度策略和经济模型的启发式调节资源价格,改进和优化计算网格资源的分配。     

基于经济的网格资源调度算法研究

网格使构建虚拟组织,在全世界范围内共享资源成为现实.但是,在网格环境下的资源管理和调度是一项相当复杂的工作,这主要是由于资源分布在世界各地,隶属于不同的组织,各个资源拥有者都有不同的使用和访问策略、开销模型、不断变化的负载和可用性.为了满足网格计算环境中资源调度的复杂需要,可以将现实世界中的经济原理和模型应用到网格环境下的任务调度中,并据此提出了几种经济资源调度算法.     

计算网格中资源调度研发现状及展望

网格在解决分散式资源共享方面具有广阔的应用前景,使得它成为下一代互联网瞩目的焦点.而计算网格为资源的需求和供给提供定量分析,激励资源拥有者加入网格的同时保证资源消费者合理有效地使用资源.介绍计算网格通用模型GRACE的基础上,针对该模型中的热点问题--资源管理和调度展开讨论,分析比较当前的几种调度方案,为进一步提出高效完备的资源调度算法作准备.     

A reputation-driven scheduler for autonomic and sustainable resource sharing in Grid computing

The obstacle for the Grid to be prevalent is the difficulty in using, configuring and maintaining it, which needs excessive IT knowledge, workload, and human intervention. At the same time, inter-operation amongst Grids is on track. To be the core of Grid systems, the resource management must be autonomic and inter-operational to be sustainable for future Grid computing. For this purpose, we introduce HOURS, a reputation-driven economic framework for Grid resource management. HOURS is designed to tackle the difficulty of automatic rescheduling, self-protection, incentives, heterogeneous resource sharing, reservation, and SLA in Grid computing. In this paper, we focus on designing a reputation-based resource scheduler, and use emulation to test its performance with real job traces and node failure traces. To describe the HOURS framework completely, a preliminary multiple-currency-based economic model is also introduced in this paper, with which future extension and improvement can be easily integrated into the framework. The results demonstrate that our scheduler can reduce the job failure rate significantly, and the average number of job resubmissions, which is the most important metric in this paper that affects the system performance and resource utilization from the perspective of users, can be reduced from 3.82 to 0.70 compared to simple sequence resource selection.     

Flexible Grid service management through resource partitioning

In this paper, a distributed and scalable Grid service management architecture is presented. The proposed architecture is capable of monitoring task submission behaviour and deriving Grid service class characteristics, for use in performing automated computational, storage and network resource-to-service partitioning. This partitioning of Grid resources amongst service classes (each service class is assigned exclusive usage of a distinct subset of the available Grid resources), along with the dynamic deployment of Grid management components dedicated and tuned to the requirements of a particular service class introduces the concept of Virtual Private Grids. We present two distinct algorithmic approaches for the resource partitioning problem, the first based on Divisible Load Theory (DLT) and the second built on Genetic Algorithms (GA). The advantages and drawbacks of each approach are discussed and their performance is evaluated on a sample Grid topology using NSGrid, an ns-2 based Grid simulator. Results show that the use of this Service Management Architecture in combination with the proposed algorithms improves computational and network resource efficiency, simplifies schedule making decisions, reduces the overall complexity of managing the Grid system, and at the same time improves Grid QoS support (with regard to job response times) by automatically assigning Grid resources to the different service classes prior to scheduling.     

Ontology‐based Grid resource management

Grid resources are typically diverse in nature with respect to their software and hardware configurations, resource usage policies and the kind of application they support. Aggregating and monitoring these resources, and discovering suitable resources for the applications become a challenging issue. This is partially due to the representation of Grid metadata supported by the existing Grid middleware which offers limited scope for matching the job requirements that directly affect scheduling decisions. This paper proposes a semantic component in conventional Grid architecture to support ontology‐based representation of Grid metadata and facilitate context‐based information retrieval that complements Grid schedulers for effective resource management. Web Ontology language is used for creating Grid resource ontology and Algernon inference engine has been used for resource discovery. This semantic component has been integrated with conventional Grid schedulers. Several experiments have also been carried out to investigate the performance overhead that arises while integrating this component with Grid schedulers. Copyright © 2009 John Wiley & Sons, Ltd.     

计算网格的资源分发和发现机制

1 引言计算网格的资源管理系统是为实现计算网格系统资源共享所应提供的最主要的服务之一。计算网格资源管理系统的基本功能是接受来自计算网格范围内的机器的资源请求,并且把特定的资源分配给资源请求者,并且合理地调度相应的资源,使请求资源的作业得以运行。资源分发、资源发现和资源的调度构成了计算网格资源管理系统的最主要的内容。资源分发和资源发现提供方法,通过该方法,在计算网格内部的机器能够形成一个可用的资源和其状态的一个视图。资源