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Decision Making in Autonomic Managers Using Fuzzy Inference System

机译:基于模糊推理系统的自主管理者决策

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Inspired from natural self-managing behavior of human body, autonomic systems promise to inject self-managing behavior in software systems. Such behavior enables self-configuration, self-healing, self-optimization and self-protection capabilities in software systems. Fuzzy inference system (FIS) is a decision methodology suitable for the vague and imprecise application domains such as software systems. Building a complete crisp rule-based system is a hard job in such complex domains because of large number of enumerations of possible rules. In literature, FIS has been successfully applied in the domains of decision analysis, automatic control and expert systems. In this paper, we have proposed to apply FIS for diagnosis and planning purposes in the autonomic manager. We implemented the proposed architecture on a simulation of autonomic forest fire application (AFFA) and achieved up to 88% accuracy.
机译:受人体自然自我管理行为的启发,自主系统有望在软件系统中注入自我管理行为。这种行为使软件系统具有自我配置,自我修复,自我优化和自我保护的功能。模糊推理系统(FIS)是一种适用于模糊和不精确的应用程序域(例如软件系统)的决策方法。在如此复杂的领域中,构建大量完整的基于规则的系统是一项艰巨的工作,因为可能规则的枚举数量很多。在文献中,FIS已成功应用于决策分析,自动控制和专家系统等领域。在本文中,我们建议在自主管理器中将FIS应用于诊断和计划目的。我们在模拟的自主森林火灾应用(AFFA)上实现了建议的体系结构,并实现了高达88%的精度。

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