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Alarm diagnosis

Network
Management
Application

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Today's large and complex telecommunication networks produce large amounts of alarms daily. An alarm is generated by a network element or its component to report an abnormal situation it has detected. Alarms are received by and handled by network management applications.

The flow of alarms from a telecommunication network contains a lot of detailed but very fragmented information about problems in the network. In fault management the alarm flow is examined, in order to isolate faults. However, the analysis is difficult, as alarms may be only remote implications of faults, and they can often be analyzed appropriately only in the context of other alarms and other knowledge. In addition, networks are large and alarms are very diverse, and alarms often occur in dense bursts. Also, networks and elements change and develop quickly.

Numerous expert systems and even specialized shells have been deviced to aid in the surveillance of alarms, aiming at alarm filtering, higher level description of network problems, and isolation of faults (see, e.g., [4] or recent articles in [9]). The development of such an expert systems is a very complex, tedious, and error-prone task. In addition to the knowledge that an expert can give, many unknown, interesting regularities may exist in the alarms.

In this paper we describe TASA, Telecommunication Alarm Sequence Analyzer, a system for taking advantage of the information potential hidden in the wealth of alarm data. (A more detailed description of TASA can be found in [3].) TASA semi-automatically discovers regularities in a sequence of alarms. The regularities can give more insight to the workings of the network, or indicate malfunctions or erroneous configurations. They can also be utilized in expert systems in alarm correlation as well as in prediction of faults. A related knowledge acquisition algorithm has been presented in [2].