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A genetic algorithm-based methodology for optimizing multiservice convergence in a metro WDM network

机译:基于遗传算法的城域WDM网络中优化多业务融合的方法

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We consider the multi-objective optimization of a multi-service arrayed-waveguide grating-based single-hop metro WDM network with the two conflicting objectives of maximizing throughput while minimizing delay. We develop and evaluate a genetic algorithm based methodology for finding the optimal throughput-delay tradeoff curve, the so-called Pareto-optimal frontier. Our methodology provides the network architecture (hardware) and the medium access control (MAC) protocol parameters that achieve the Pareto-optima in a computationally efficient manner. The numerical results obtained with our methodology provide the Pareto-optimal network planning and operation solutions for a wide range of traffic scenarios. The presented methodology is applicable to other networks with a similar throughput-delay tradeoff.
机译:我们考虑了基于多业务阵列波导光栅的单跳城域WDM网络的多目标优化,这两个目标相互冲突,即在最大化吞吐量的同时最小化延迟。我们开发和评估基于遗传算法的方法,以找到最佳的吞吐量-延迟权衡曲线,即所谓的帕累托最优边界。我们的方法论提供了网络架构(硬件)和媒体访问控制(MAC)协议参数,这些参数以计算有效的方式实现了帕累托最优。通过我们的方法获得的数值结果为各种交通场景提供了帕累托最优网络规划和运营解决方案。所提出的方法适用于具有类似吞吐量-延迟权衡的其他网络。

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