Chapter 10 Conclusion
Correlating alarms is a task that requires good working knowledge
of the system in question. In building a program to take care of
monitoring a network a prime consideration should be how to make
the system easy to update. This is especially important in the
rapidly changing environment of a telecommunications network.
Getting this knowledge into a computer program is one part of the
programming process. This thesis has discussed ways to start a
knowledge base from a model of the network. There is work on
maintaining a knowledge base through repeatedly generating new
knowledge bases for each change. This way is a little drastic and
not a satisfying solution to the problem.
The way to maintain a knowledge base, chosen for the
implementation, was Ripple-Down Rules. This serves to place each
rule in the context for which it was written. The structure may
be limiting, but the benefits are great. Maintenance can be
carried out on a daily basis by the network operator. This is a
great improvement over conventional production systems which
require a programmer to implement modifications plus extensive
testing to make sure the system still works.
10.1 Contributions made
To my knowledge, Ripple-Down Rules has not been applied to network
fault management. The closest would be the help desk for the unix
system [Compton, 2000]. But a help desk is not the same as a network
monitor. Compton himself, the great authority on RDR,
has not heard of a case like it.
As shown in this paper, the existing methods of maintaining a
rules base are inadequate. The very idea of stand alone rules
controlled by consistency checking and conflict resolution is
difficult to make accurate and make easy to update. Ripple-Down
Rules seems to hold the answer.
Another branch of my work was to venture into the world of Machine
Learning. The problem with starting an RDR knowledge base from
scratch is, well, that you have to start from scratch. Machine
Learning helps to bridge the gap between having some concepts and
having the start of a good rules base.