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Performance analysis of limited number of wavelength converters by share per node in optical switching network

机译:光交换网络中按节点数分配的有限数量的波长转换器的性能分析

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In this paper, we present studies of an optical switching (OS) node utilizing a limited number of WCs (wavelength converters) in order to reduce the implementation cost of an OS node. The study stems from practical observation that WCs are expensive. Consequently, each output wavelength may not necessarily have its own WC and has to share a limited pool of WCs with other output wavelengths. In order to improve the utilization of the limited number of WCs, a share per node (SPN) method is proposed for the OBS node. Subsequently, a multi-dimensional Markov chain model of SPN is presented to evaluate its performance. To reduce the complexity of the multi-dimension Markov analysis, we propose a suite of methods, called randomized states (RS) multi-plane Markov chain analysis, followed by self-constrained iteration (SCI) and eventually ending with the sliding window (SW) update method, to solve for the solution. Numerical results are presented to verify the accuracy of the analytical model. With SPN, about 50% and 80% of WCs can be saved in high load and low load scenarios respectively.
机译:在本文中,我们目前对利用有限数量的WC(波长转换器)的光交换(OS)节点进行研究,以降低OS节点的实现成本。该研究源于实际观察到的WC昂贵。因此,每个输出波长可能不一定具有自己的WC,而必须与其他输出波长共享有限的WC库。为了提高有限数量的WC的利用率,提出了一种针对OBS节点的每节点共享(SPN)方法。随后,提出了SPN的多维马尔可夫链模型来评估其性能。为了降低多维马尔可夫分析的复杂性,我们提出了一套方法,称为随机状态(RS)多平面马尔可夫链分析,然后进行自约束迭代(SCI),最后以滑动窗口(SW)结尾)更新方法,以解决问题。数值结果表明了分析模型的准确性。使用SPN,分别在高负载和低负载情况下可以节省大约50%和80%的WC。

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