A Knowledge-Based System for Network Communication Design
Networks are the mainstay of modern-day communications. Their use in transporting voice, pictures, and data is constantly increasing. Applications in the areas of computer communications, teleprocessing, and teleconferencing are finding wide markets. The thrust of current research in communication networks is lower costs. Attempts to integrate voice and data, exploit optical fibres and satellite technology, and optimize network topologies and hardware are steps in this direction. This work attempts to apply the current paradigms in Artificial Intelligence research to the problems in network optimization. The experience AI researchers have gained in organizing and using knowledge to solve problems (Ref. 1,2) is especially relevant in this work.
Unable to display preview. Download preview PDF.
- 1.Mylopolous, J., et al., “Building Knowledge—Based Systems: The PSN Experience,” Computer, October 1983.Google Scholar
- 2.Levesque, H. J., and R. J. Brachman, A Fundamental Tradeoff in Knowledge Representation and Reasoning, Readings in Knowledge Representation, editors, R. J. Brachman and H. J. Levesque, Morgan Kaufmann Publishers, Inc., 1985.Google Scholar
- 3.Gerla, M., H. Frank, W. Chou, J. Eckl, “Cut Saturation Algorithm for the Topological Design of Packet—switched Communication Networks,” Proceedings of the NTC 1974.Google Scholar
- 4.Kerchenbaum, A., W. Chou, “A Unified Algorithm for Designing Multidrop Teleprocessing Networks,” IEEE Transactions on Communications Volume 22, No. 11, November, 1974.Google Scholar
- 5.Karlgaard, David, Osama Mowafi, Paul Rice, “ASSET—A Set of Automated Network Design and Performance Management Tools,” IEEE Transactions, 1982.Google Scholar