基于多代理的网络故障检测新方法

A New Network Troubleshooting Method Based on Multi-agent

针对现有网络故障诊断系统的局限性和故障模式的不同特征,在模糊神经网络技术中引入粗糙集理论进行诊断,提出了基于Agent的分布式网络故障诊断模型。在模型中设计了一种新的算法———健壮网络故障诊断神经网络(RNFNN),利用网络的拓扑结构和权值分布实现非线性映射,从而大大改进了诊断性能。模型采用一定的状态检查策略和验证机制,保证了Agent的自身安全和通信安全。该模型与特定的系统应用环境无关,因此,提供了一个通用的网络故障诊断系统框架。实验表明,利用该方法实现的系统在进行网络故障诊断时可以取得较好的效果。

To overcome the limits of present network fault diagnosis systems and the difficulty of different fault patterns, a distributed network fault diagnosis framework based on multi-agent was proposed. In the framework, combined fuzzy neural network with rough sets theory, a new algorithm-RNFNN was presented, which greatly improves the performance of the system, with a nonlinear mapping realized by using topological structures and weights of the FNN. Also, the state-checking and authentication mechanism ensure the security of the agents and their communication. The framework is environment-independent, thus providing a general-purpose heterogeneous network fault diagnosis. The experiment result of this framework shows a good diagnostic ability.