Abstract
The design of optical networks for maximum throughput under diverse traffic demands is a long-standing NP-hard problem. In this paper, by parameterizing the relationship between the network topology and traffic demand, a polynomial-time objective function, the demand weighted cost (DWC), is introduced and evaluated for different scale networks and diverse traffic scenarios. It is shown that the proposed DWC is highly correlated to network throughput, while speeding up the topology evaluation process by some five to six orders of magnitude. The DWC was then applied as the optimization target with three different topology optimization algorithms (DWC-selection, genetic algorithm, and our hierarchical topology design), achieving 90% and 460% throughput increases, on average, for small-scale (14-node) and large-scale (100-node) topology designs, respectively. The proposed methods have the potential of maximizing throughput in the design of future optical network topologies.
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