基于策略的上下文感知自我管理模型

T. Cioara, I. Anghel, I. Salomie, M. Dînsoreanu
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引用次数: 11

摘要

本文提出了一种基于通用策略的自我管理模型,可用于自动检测和修复上下文适应过程中出现的问题。为了成功地捕获和评估管理上下文感知适应过程的动态规则,我们定义了一个通用的上下文策略表示模型及其相关的推理语言转换模型,用于运行时评估。为了评估尊重上下文策略的运行时程度,我们定义并形式化了上下文熵的概念。使用RAP(资源、参与者、策略)上下文模型提供的基于集合和基于本体的表示,以系统编程的方式对上下文信息进行建模。上下文模型构件由基于BDI (Believe, Desire, Intentions)代理的管理基础设施在运行时生成和管理。该模型在我们的分布式系统研究实验室智能环境中进行了测试和验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Policy-Based Context Aware Self-Management Model
This paper proposes a generic policy based self-management model that can be used to automatically detect and repair the problems appeared during the context adaptation processes. To successfully capture and evaluate the dynamic rules that govern the context aware adaptation processes we have defined an generic context policy representation model and its associated reasoning language conversion model for run-time evaluation. To evaluate the run-time degree of respecting the context policies we define and formalize the concept of context entropy. The context information is modeled in a system programmatic manner using both the set based and ontology based representations provided by our RAP (Resources, Actors, Policies) context model. The context model artifacts are generated and administrated at run time by a management infrastructure based on BDI (Believe, Desire, Intentions) agents. The model was tested and validated within the premises of our Distributed Systems Research Laboratory smart environment.
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