Mobile Agents for Network Fault Detection Based on The Wiener Filter

Existing centralized based network management approaches suffer from problems such as insufficient scalability, availability and flexibility, as networks become more distributed. Mobile Agents (MA), upgraded with intelligence, can present a reasonable new technology that will help to achieve distributed management. These agents migrate from one node to another, accessing an appropriate subset of MIB variables from each node analysing them locally and retaining the results of this analysis during their subsequence migration. One of the network fault management tasks is fault detection, and in this work we purpose statistical method based on Wiener filter to capture the abnormal changes in the behaviour of the MIB variables. my algorithm was implemented on data obtained from two different scenarios in the laboratory, with four different fault case studies. The purpose of this is to provide the manager node with a high level of information, such as a set of conclusions or recommendations, rather than large volumes of data relating to each management task.