R. Matsumura et O. Miyagishi, SPECIFICATION DESCRIPTION SUPPORTING METHOD OF TELECOMMUNICATIONS NETWORKS MANAGEMENT USING INFORMATION MODEL AND PROCESS MODEL, IEICE transactions on communications, E78B(1), 1995, pp. 39-46
Managed Objects (MOs) can be specified by the combination of a static
information model and a dynamic process model. First, this paper prese
nts a mapping of attributes from a process model diagram to an informa
tion model diagram. Then, it introduces a concept of topology into the
se two models and proposes a hypothesis about the relationship of topo
logy in these two models. To explicitly explain the hypothesis, it can
be stated that all attributes of incoming or outgoing data related to
a process in a process model are mapped to an information model where
these attributes are interconnected by an explicit relationship which
corresponds to a specific meaning, such as physical containment or lo
gical connection. From an intuitive perspective, it can be said that i
f two attributes have a close topological relationship in a process mo
del, the mapped attributes also have a close topological relationship
in an information model. This hypothesis provides clues for determinin
g whether there is an error in an attribute either in the process mode
l or in the information model. By examining the way attributes of inco
ming or outgoing data related to a process are mapped to an informatio
n model, we can detect whether there is an error with respect to the p
rocess. The error correction is performed with the assistance of proba
bility analysis. The method of error detection and correction can be i
mplemented in a computer aided tool. Then, error detection on the attr
ibute level becomes automatic, and error correction on the attribute l
evel becomes interactive through the computer aided tool. Finally, the
validity of the hypothesis is confirmed by analyzing ITU-T Recommenda
tion M.3100. The specification of the fabric object class defined in M
.3100 is transformed into these two models and the hypothesis is valid
ated for the analysis of the mapping between these two models.