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The Embodiment of Autonomic Computing in the Middleware for Distributed System with Bayesian Networks

机译:贝叶斯网络在分布式系统中间件中自主计算的体现

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摘要

In this paper, we propose an intelligent middleware framework based on the concept of the autonomic computing. Because decisions for optimizing a system are highly dependent on the status of the system in the near future, predictions of the status can boost up the performance of system. Bayesian networks that are frequently used in the domain of user modeling are adopted as a diagnosis engine. Since there are many different kinds of behavioral patterns, it is impossible to model all of them into a single model. A Bayesian network is learned for each typical behavioral pattern. Experimental results show that the proposed method offers a promising way of intelligent middlewares.
机译:在本文中,我们提出了一种基于自主计算概念的智能中间件框架。由于在不久的将来优化系统的决策高度依赖于系统的状态,因此状态的预测可以提高系统的性能。在用户建模领域中经常使用的贝叶斯网络被用作诊断引擎。由于存在多种不同的行为模式,因此无法将所有行为模式都建模为一个模型。针对每种典型的行为模式学习贝叶斯网络。实验结果表明,该方法为智能中间件提供了一种有希望的方法。

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