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Behavioral modeling and formal verification of a resource discovery approach in Grid computing

机译:网格计算中资源发现方法的行为建模和形式验证

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Grid computing is the federation of resources from multiple locations to facilitate resource sharing and problem solving over the Internet. The challenge of finding services or resources in Grid environments has recently been the subject of many papers and researches. These researches and papers evaluate their approaches only by simulation and experiments. Therefore, it is possible that some part of the state space of the problem is not analyzed and checked well. To overcome this defect, model checking as an automatic technique for the verification of the systems is a suitable solution. In this paper, an adopted type of resource discovery approach to address multi-attribute and range queries has been presented. Unlike the papers in this scope, this paper decouple resource discovery behavior model to data gathering, discovery and control behavior. Also it facilitates the mapping process between three behaviors by means of the formal verification approach based on Binary Decision Diagram (BDD). The formal approach extracts the expected properties of resource discovery approach from control behavior in the form of CTL and LTL temporal logic formulas, and verifies the properties in data gathering and discovery behaviors comprehensively. Moreover, analyzing and evaluating the logical problems such as soundness, completeness, and consistency of the considered resource discovery approach is provided. To implement the behavior models of resource discovery approach the ArgoUML tool and the NuSMV model checker are employed. The results show that the adopted resource discovery approach can discovers multi-attribute and range queries very fast and detects logical problems such as soundness, completeness, and consistency.
机译:网格计算是来自多个位置的资源的联合,以促进Internet上的资源共享和问题解决。在网格环境中寻找服务或资源的挑战最近成为许多论文和研究的主题。这些研究和论文仅通过仿真和实验来评估其方法。因此,可能无法很好地分析和检查问题的状态空间的某些部分。为了克服此缺陷,将模型检查作为一种用于验证系统的自动技术是一种合适的解决方案。在本文中,提出了一种用于解决多属性和范围查询的资源发现方法。与该范围的论文不同,本文将资源发现行为模型与数据收集,发现和控制行为分离。它还通过基于二元决策图(BDD)的形式验证方法,促进了三种行为之间的映射过程。形式化方法从控制行为中以CTL和LTL时间逻辑公式的形式提取资源发现方法的预期属性,并全面验证数据收集和发现行为中的属性。此外,提供了对所考虑的资源发现方法的合理性,完整性和一致性等逻辑问题的分析和评估。为了实现资源发现方法的行为模型,使用了ArgoUML工具和NuSMV模型检查器。结果表明,采用的资源发现方法可以快速发现多属性和范围查询,并可以检测逻辑问题,例如完整性,完整性和一致性。

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