Grid computing is highly dynamic in nature where resources are subject to change due to performance degradation and node failure. The resources include processing elements, storage, network, and so on; they come from the interconnection of parallel machines, clusters, or any workstation. One of the main properties of these resources is to have changing characteristics even during the execution of an application. Thus, resource usage by applications cannot be static during run-time; neither can change in resources be considered as faults. Therefore, Grrid application designers must keep in mind that resources and resource management are highly dynamic within Grid architectures. Grdi resource brokering is introduced to simplify resource discovery, selection, and job submission for Grid application. However, it is the responsibility of a Grid resource broker to distribute jobs among heterogeneous resources and optimise the resource usage. As a result, a Grid resource broker should have the capablility to adapt to these changes and take appropriate actions to improve performance of various computing applications. To adapt to the Grid resource changes, an adaptive service is introduced in this research. The adaptive service consists of a monitoring tool, decision manager, and migration engine to ensure the job finishes at the time specified. The adaptive service supports job migration during run-time to ensure timely job completion. Our work in this research shows a Grid test-bed and White Rose Grid implementation of an adaptive service that supports job migration during run-time to ensure timely job completion. Performance prediction is used to estimate expected job completion time and determine whether any onserved performance degradation is likely to result in failure to meet a user specified deadline. A key feature of our approach is that the user is not required to install additional software or make complex alterations to their code requiring specialist Grid computing knowledge. This is achieved using a reflective technique to bind the adaptive service components to the user's code. Also, this research proves the adaptive service overhead is very minimal. The adaptive service is a viable contender for future Grid resource brokering implementation.
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机译:网格计算本质上是高度动态的,其中资源会由于性能下降和节点故障而发生变化。资源包括处理元素,存储,网络等。它们来自并行计算机,集群或任何工作站的互连。这些资源的主要特性之一是即使在执行应用程序期间也具有变化的特性。因此,应用程序对资源的使用在运行时不能是静态的。资源变化均不能视为故障。因此,Grrid应用程序设计人员必须牢记,资源和资源管理在Grid体系结构中是高度动态的。引入了Grdi资源代理,以简化Grid应用程序的资源发现,选择和作业提交。但是,网格资源代理负责在异构资源之间分配作业并优化资源使用。因此,网格资源代理应该具有适应这些更改并采取适当措施来提高各种计算应用程序性能的能力。为了适应网格资源的变化,本研究引入了一种自适应服务。自适应服务包括监视工具,决策管理器和迁移引擎,以确保作业在指定的时间完成。自适应服务在运行时支持作业迁移,以确保及时完成作业。我们在这项研究中的工作显示了自适应服务的Grid测试平台和White Rose Grid实施,该服务在运行时支持作业迁移以确保及时完成作业。性能预测用于估计预期的工作完成时间,并确定任何保留的性能下降是否有可能导致未能满足用户指定的期限。我们方法的主要特点是不需要用户安装其他软件或对其代码进行复杂的更改,而无需专业的网格计算知识。这是通过使用反射技术将自适应服务组件绑定到用户代码来实现的。而且,这项研究证明自适应服务开销非常小。自适应服务是未来Grid资源代理实现的可行竞争者。
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