Application of AI/OR Techniques for evaluating performance of large scale computer network

This thesis introduces two models to analyze the complex network (i.e. networkwith large nodes and links).In the first model we will develop an expert system that helps in analysis andevaluation of large-scale computer networks. The objectives of this system are to:Minimize the total network probability of failure, delay and cost of thenetworks links.Maximize the traffic flow inside the network.The system to be developed will offer the following capabilities:l)It will establish and build a database for the characteristics and attributes of thenetwork under investigation allowing dynamic adaptation to any changes inthe network data such as addition and/or deletion of nodes and/or links.2)It will provide a complete visibility about the network under study by showingthe network topology line graph and displaying the network data andattributes.3)It will perform knowledge acquisition to have information that reflect thebehavior of the network and performance attributes at each node of thenetwork.4)It will provide an expert system that can be consulted to show graphs anddisplay information about the network performance attributes through thefollowing two analysis modes: