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The design of a novel context-aware policy model to support machine-based learning and reasoning

机译:一种新颖的上下文感知策略模型的设计,以支持基于机器的学习和推理

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摘要

The purpose of autonomic networking is to manage the business and technical complexity of networked components and systems. However, the lack of a common lingua franca makes it impossible to use vendor-specific network management data to ascertain the state of the network at any given time. Furthermore, the tools used to analyze management data are all different, and hence require different data in different formats. This complicates the construction of context from diverse information sources. This paper describes a new version of the DEN-ng context-aware policy model, which is part of the FOCALE autonomic network architecture. This model has been built using three guiding principles: (1) both the context model and the policy model are rooted in information models, so that they can govern managed entities, (2) each model is expressly constructed to facilitate the generation of ontologies, so that reasoning about policies constructed from the model may be done, and (3) the model is expressly constructed so that a policy language that supports machine-based reasoning and learning can be developed from it.
机译:自主网络的目的是管理网络组件和系统的业务和技术复杂性。但是,由于缺少通用的通用语言,因此无法在任何给定时间使用特定于供应商的网络管理数据来确定网络状态。此外,用于分析管理数据的工具都是不同的,因此需要使用不同格式的不同数据。这使来自各种信息源的上下文构造变得复杂。本文介绍了DEN-ng上下文感知策略模型的新版本,该模型是FOCALE自主网络体系结构的一部分。该模型是根据以下三个指导原则构建的:(1)上下文模型和策略模型都植根于信息模型中,以便它们可以管理受管实体;(2)每个模型都经过明确构造,以促进本体的生成;这样就可以对由模型构建的策略进行推理,并且(3)明确构建模型,以便可以从中开发支持基于机器的推理和学习的策略语言。

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