An Adaptive Multi-Agent Approach for Distributed Alarm Correlation and Fault Identification

A.A Mohamed and O. Basir (Canada)


Distributed fault management, computer networks, alarm correlation, evidential reasoning


Network fault management systems rely heavily on observed alarms to identify the root causes of network failures. Due to the increasing complexity of modern computer networks, the information carried by these alarms may in fact be vague, imprecise, and inconsistent. Thus, these alarms often possess different diagnostic capabilities and should not be treated equally. In this paper, we propose a new distributed alarm correlation approach that effectively tackles the aforementioned data deficiencies. According to the proposed approach, the managed network is first divided into a disjoint set of management domains and each domain is assigned an intelligent agent. Within the framework of Dempster Shafer evidence theory, the intelligent agent perceives each network entity in its domain as a source of information. As such, alarms emitted by these entities are expected to exhibit different information qualities and are assigned different weights accordingly. Based on their weights, the observed alarms are then correlated by their respective agent into a single local fuzzy composite alarm. Since local composite alarms constitute only partial views of the managed network, they are correlated, by a higher management entity, into a global alarm that accurately reflects a comprehensive view of the managed network.

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