Presents an approach for modeling and solving the problem of fault identification and alarm correlation in large communication networks. A single fault in a large network may result in a large number of alarms, and it is often very difficult to isolate the true cause of the fault. This appears to be one of the most important difficulties in managing faults in today's networks. The problem may become worse in the case of multiple faults. The authors present a general methodology for solving the alarm correlation and fault identification problem. They propose a new alarm structure, propose a general model for representing the network, and give two algorithms which can solve the alarm correlation and fault identification problem in the presence of multiple faults. These algorithms differ in the degree of accuracy achieved in identifying the fault, and in the degree of complexity required for implementation.>

A report is presented on efforts to develop and manage a model of a real-time computer system. The computer systems of interest are large-scale, IBM mainframe computers that run the MVS operating system. The model interacts with both the computer system itself, and with heterogeneous software modules designed to control and manage the computer system. The work indicates that even in rule-based environments, an object-oriented status-model manager provides valuable functionality.>