基于贝叶斯分类的分布式网络故障诊断模型

该文提出了一个基于Agent的分布式网络故障诊断系统模型框架，该模型对贝叶斯分类理论进行了推广。模型将先验知识和观察数据结合起来，从而大大改进了系统的诊断性能。模型采用一定的状态检查和验证策略，保证了Agent的自身安全和通信安全。Agent之间各自独立，相互协作，合作完成诊断任务。该模型与特定的系统应用环境无关。因此，该文提供了一个通用的网络故障诊断系统框架。

A Distributed Network Fault Diagnosis Model Based on Bayesian Classification

A framework model proposed in this paper is a distributed network diagnosis sysfem based on Agent,which extends Bayesian Classification Theory.The prior knowledge could be combined with observed data,which greatly improves the performance of the system.The static-checking and policy of authentication mechanism ensure the security of the agents themselves and the communication among them.Agents are independent but are capable of communication with each other when they work their actions.The model is independent of specific application environment,thus providing a general framework for network fault diagnosis.