Abstract

This thesis proposes a general model for telecommunications networks and, from this model, it proposes a model for alarm correlation in the network as a whole. The model is based on a principle named recursive multifocal correlation, also developed in this thesis, according to which the telecommunications network is partitioned into several sub-networks, each one of them constituting a correlation focus. The breakdown of the problem into smaller sub-problems facilitates its solution and allows the use, in each sub-network, of the correlation technique most suitable to its peculiarities. The multifocal correlation principle may be recursively utilized in each sub-network until the network element level is reached. The concepts developed were utilized in the implementation of a prototype, used for alarm correlation in a canonical telecommunications network. By utilizing a commercial product as a tool for the development and evaluation of Bayesian networks, the occurrence of alarms was simulated and the functioning of the model was verified, both concerning the identification of the possible causes for the received alarms (diagnostic inference), as in the prediction of possible effects (predictive inference).

Citations