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Model-driven Engineering of Decentralized Control in Cyber-Physical Systems

机译:网络物理系统分散控制的模型驱动工程

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Self-adaptation is nowadays recognized as an effective approach to manage the complexity and dynamics inherent to cyber-physical systems, which are composed of deeply intertwined physical and software components interacting with each other. A self-adaptive system typically consists of a managed subsystem and a managing subsystem that implements the adaptation logic by means of the well established MAPE-K control loop. Since in large distributed settings centralized control is hardly adequate to manage the whole system, self-adaptation should be achieved through collective decentralized control, that is multiple cyber-physical entities must adapt in order to address critical runtime conditions. Developing such systems is challenging, as several dimensions concerning both the cyber-physical system and the decentralized control loop should be considered. To this end, we promote MAPE-K components as first-class modeling abstractions and provide a framework supporting the design, development, and validation of decentralized self-adaptive cyber-physical systems.
机译:现在,自适应被认为是管理网络物理系统固有的复杂性和动态的有效方法,这些方法由深度交织的物理和软件组件彼此交互。自适应系统通常由托管子系统和管理子系统组成,该管理子系统通过建立的Mape-K控制循环实现自适应逻辑。由于在大型分布式设置中集中控制几乎不足以管理整个系统,因此应通过集体分散控制来实现自适应,即多个网络物理实体必须适应以解决关键的运行时条件。发展此类系统是具有挑战性的,因为应该考虑有关网络物理系统和分散控制环路的几个维度。为此,我们将Mape-K组件推广为一流的建模抽象,并提供支持分散的自适应网络系统的设计,开发和验证的框架。

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