网格环境下基于策略的语义资源匹配器

S. Mahmood, H. F. Ahmed, R. ur Rasool, K. Qadir
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引用次数: 1

摘要

在网格计算中,不同的虚拟组织提供不同类型的资源。他们还想对资源的使用加以限制。为此,它们指定了资源使用策略。这些策略针对不同类型的用户和人群是不同的。要提交作业,用户首先使用语义matchmaker选择执行作业所需的资源,然后提交作业。策略在资源提供者端针对用户强制执行。现在,在提交作业之前,用户不知道是否允许他使用所需的资源和服务及其各自的功能。因此,用户作业可能会被拒绝执行,并且之前的选择工作被浪费了。这消耗了用户的时间。为了克服这一问题,本文提出了一种基于策略的语义资源匹配器(PBSRM),它具有网格资源和服务及其使用策略的语义知识库。策略优化发现过程。策略分析器在发现过程中针对不同类型的用户执行这些策略。它还有助于控制用户想要在服务上执行的操作。现在,通过使用PBSRM资源,用户只能获得他们被允许使用的资源和服务。这节省了他们的时间,因为他们非常确定在选定的资源上执行他们的作业。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Policy-Based Semantic Resource Matchmaker for Grid Environment
In Grid computing different virtual organization provides different types of resources. They also want to put some limitation on the usage of their resources. For this purpose they specify resource usage policies. These policies are different for different type of users and group of people. To submit a job, user first selects resources, required for the execution of the job using semantic matchmaker and then submits the job. Policies are enforced with respect to user at resource provider end. Now before submitting job user has no idea whether he is allowed to use the required resources and services with their respective functionalities. As a result of which user job may be rejected to execute and prior selection effort is wasted. This dissipates user time. In order to overcome this, in this paper we propose a Policy-Based Semantic Resource Matchmaker (PBSRM) that has a semantic knowledge base of Grid resources and services as well as their usage policies. Policies optimize the discovery process. A policy analyzer enforces these policies in the discovery process with respect to different types of users. It also helps to control the actions that user wants to perform on the services. Now by using PBSRM resource users get only those resources and services for which they are permitted to use. This saves their time, since they are much sure about the execution of their jobs on selected resources.
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