Abstract

The area of telecommunications network design and management is complex and solutions can become algorithmically intractable for moderately large networks. It is, therefore, a promising applications area for expert systems; however, a survey of the published literature reveals a paucity of integrated systems combining design and optimization of network-based problems. We present a distributed expert telecommunications provisioning system which uses a simulation-based optimization methodology for queueing networks. Our architecture admits parallel simulation of multiple configurations. A knowledge-based search drives our performance optimization of the network. The search process is a randomized combination of Steepest Descent and Branch and Bound algorithms, where the generating function of new states uses qualitative reasoning, and the gradient of the objective function is estimated using a heuristic Score Function method. We found a random search based on the relative order of the performance gradient components to be a powerful qualitative reasoning technique. The system (P3) is implemented as a loosely coupled expert system with components written in PROLOG, SIMSCRIPT, and C. We demonstrate the efficacy of our method through an example from the domain of Jackson queueing networks.