Reliability and Fault Tolerance based Topological Optimization of Computer Networks - Part II: Iterative Techniques

Topological optimization of computer networks is concerned with the selection of a subset of the available links such that the reliability and fault-tolerance aspects are maximized while meeting a cost constraint. In this case, the problem is stated as optimizing the reliability and fault-tolerance of a network subject to a maximum cost constraint. Existing iterative-based techniques consider the simple single-objective version of the problem by considering reliability as the only objective. We consider fault-tolerance to be an important network design aspect. We consider the use of three iterative techniques, namely Tabu Search, Simulated Anealing, and Genetic Algorithms, in solving the multi-objective topological optimization network design problem. Experimental results for a set of 10 randomly generated networks using the three iterative techniques are presented and compared. It is shown that improving the fault tolerance of a network can be achieved while optimizing its reliability however at the expense of a reasonable increase in the overall cost of the network.