摘要
提出一种新的基于分布智能传播的自动故障管理系统(AFMDIP),该系统采用人工智能和网络分布管理技术,引入协作代理,提高了系统数据采集能力.代理用神经网络和事例暂存库进行告警收集、分类和事例管理.域内的故障首先由代理进行诊断,域内不能解决的问题将提交给管理中心.管理中心综合考虑各个域的信息,进行基于事例推理的故障诊断,并将事例传播到代理中.后续的类似故障将由代理直接完成诊断,提高了故障管理的效率,达到了信息和事例共享的目的.实验证明,AFMDIP有效降低了管理中心的带宽消耗,提高了在大范围多故障情况下的故障诊断速度.
An automated fault management system based on distributed intelligent propagation (AFM-DIP) is presented by using the techniques of artificial intelligence and distributed network management. The cooperative agents are introduced to improve the ability of system's data collection. Neural networks and temporary cases database are applied by agents for alarm collection, classification and cases management. The agents diagnose the faults in a domain, and the unsolved problems would be submitted to the management center that will diagnose the fault based on the case based reasoning after analyzing all the information from each domain, and then transmit this case to the agents. The consequent similar faults will be diagnosed directly by the agents, so the efficiency of the fault management is increased. The information and cases sharing can be achieved. The experiment shows that the AFMDIP reduces the bandwidth consume in the management center and speeds up the fault diagnosis process under large-scale and multi-faults situations.
出处
《西安交通大学学报》
EI
CAS
CSCD
北大核心
2004年第2期115-118,148,共5页
Journal of Xi'an Jiaotong University
基金
国家"八六三"网络安全管理与测评技术基金资助项目 (863 - 3 0 1 - 0 5- 0 3 )
国家"九五"科技攻关基金资助项目 (96- 743- 0 1 - 0 4- 0 1 ).
关键词
故障管理
神经网络
基于事例推理
代理
Agents
Artificial intelligence
Computer simulation
Data acquisition
Expert systems
Management
