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Maximizing Revenue With Adaptive Modulation And Multiple FEC In Flexible Optical Networks

Cao Chen, Fen Zhou, S. Xiao
Published 2019 · Computer Science

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With high spectrum efficiency, flexible optical networks are preferred to accommodate the increasing heterogeneous traffic in present-day Internet. However, due to resource crunch issue, not all services can be satisfied at the same time. As each satisfied service is supposed to bring a revenue for the network, the resource crunch will lead to network revenue loss. Given a set of service requests to be provisioned in a flexible optical network, we consider the problem of maximizing the network revenue subject to the physical layer constraint and limited spectrum resource. To mitigate the impact of non-linear interference and assure the quality of transmission, adaptive modulation and FEC are employed. Thus, we formulate a joint optimization problem consisting of routing, modulation, FEC and spectrum assignment. To solve it efficiently, a fast two-phase heuristic algorithm is proposed, which is shown to be near-optimal for revenue maximization. By simulations, we demonstrate that both adaptive modulation and multiple FEC enable to improve significantly the network revenue: Adaptive modulation is preferred in networks with a high signal-to-noise ratio (SNR); while using multiple FEC is more profitable for scenarios with a low SNR.
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