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A Technique for Measuring the Level of Autonomicity of Self-managing Systems

机译:一种测量自我管理系统自主性水平的技术

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Autonomic and self-managing systems are increasingly pervasive across an ever-widening spectrum of application domains. Autonomic technology is advancing at a high rate, yet there are no universal standards for the technology itself and the design methods used. There are also significant limitations to the way in which these systems are validated, with heavy reliance on traditional design-time techniques, despite the highly dynamic behaviour of these systems in dealing with run-time configuration changes and environmental and context changes. These limitations ultimately undermine the trustability of these systems and are barriers to eventual certification. This paper is concerned with setting the groundwork for the introduction of standards for Autonomic Computing (AC), in terms of technologies and the composition of functionality as well as validation methodologies. We propose that the first vital step in this chain is to introduce robust techniques by which the systems can be described in universal language, starting with a description of, and means to measure the extent of autonomicity exhibited by a particular system We present a novel technique for measuring the Level of Autonomicity (LoA) along several dimensions of autonomic system self-CHOP (self-configuration, self-healing, self-optimisation and self-protection) functionalities.
机译:自主和自我管理系统越来越普遍地遍布应用领域的常见频谱。自主技术以高速推进,但该技术本身并无普遍标准和使用的设计方法。尽管这些系统的高度动态行为在处理运行时配置更改和环境和环境和环境变化时,验证了这些系统的验证方式也存在显着的依据。这些限制最终破坏了这些系统的可信度,并且是最终认证的障碍。本文涉及在技术和验证方法的技术和验证方法方面设定引入自主计算(AC)标准的基础。我们提出该链中的第一步是引入稳健的技术,通过该技术可以以通用语言描述,从描述开始,并且手段测量特定系统所呈现的自主性程度我们提出了一种新颖的技术用于沿着自主系统自主(自我配置,自我修复,自我优化和自我保护)功能的几个维度测量自主神经程度(LOA)的水平。

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