Title :
A pragmatic approach for feature interaction detection in intelligent networks
Author :
Sefidcon, A. ; Khendek, F.
Author_Institution :
Dept. of Electr. & Comput. Eng., Concordia Univ., Montreal, Que., Canada
Abstract :
A new pragmatic approach for feature interaction (FI) detection for intelligent networks (IN) is presented in this paper. In this approach, the causes of FI given in Bellcore and European benchmarks serve as the starting point. The necessary information for feature description is derived from these causes. This information is modelled using an object-oriented template. Features are described in terms of necessary resources and actions. The detection algorithm takes this information as input and checks for interactions between features. The algorithm consists of three parts: filtering, feature instantiation and detection. Using the filtering method, all the possible interaction-prone scenarios are produced and using the list of topologically different call combinations the actual features are instantiated. The detection algorithm is run on these actual participants of the features in order to detect interactions. We applied our approach to the feature interaction benchmarks
Keywords :
intelligent networks; object-oriented methods; Bellcore benchmarks; European benchmarks; IN; call combinations; detection algorithm; feature instantiation; feature interaction detection; filtering; intelligent networks; object-oriented template; Computer networks; Computer vision; Detection algorithms; Filtering algorithms; Intelligent networks; Logic; Object oriented modeling; Telephony;
Conference_Titel :
Computer Communications and Networks, 1999. Proceedings. Eight International Conference on
Conference_Location :
Boston, MA
Print_ISBN :
0-7803-5794-9
DOI :
10.1109/ICCCN.1999.805583