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The basic problem in optimizing communication networks is to assign a proper circuit for each origin destination pair in networks so as to minimize the average network delay, and the network optimal route selection model is a multi constrained 0 1 nonlinear programming problem. In this paper, a new stochastic optimization algorithm, Immune Algorithm, is applied to solve the optimization problem in communication networks. And the backbone network vBNS is chosen to illustrate the technique of evaluating delay in a virtual network. At last, IA is compared with the optimization method in communication networks based on Genetic Algorithm, and the result shows that IA is better than GA in global optimum finding.
The basic problem in optimizing communication networks is to assign a proper circuit for each origin destination pair in networks so as to minimize the average network delay, and the network optimal route selection model is a multi-constrained 0 1 nonlinear programming problem. In this paper, a new stochastic optimization algorithm, Immune Algorithm, is applied to solve the optimization problem in communication networks. And the backbone network vBNS is chosen to illustrate the technique of evaluating delay in a virtual network. At last, IA is compared with the optimization method in communication networks based on Genetic Algorithm, and the result shows that IA is better than GA in global optimum finding.