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A methodology to design the link cost functions for impairment aware routing algorithms in optical networks

机译:为光网络中的减损感知路由算法设计链路成本函数的方法

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We propose a methodology to design the link cost function and, consequently, a systematic form to design a RWA algorithm. We call this methodology link cost function design (LCFD) and it consists of four steps: The choice of the link cost function input variables, the expansion of the cost function in terms of a series of functions, the selection of an overall network performance indicator as the optimization target, and finally, the execution of an optimization process to find the series coefficients that optimize the network performance indicator based on off-line network simulations. The optimization process is performed by a computational intelligence technique, the particle swarm optimization. The proposed methodology (LCFD) is used to design an adaptive IA-RWA algorithm, which we call Power Series Routing (PSR). The effectiveness of both methodology and IA-RWA algorithm is investigated. The PSR is compared with other algorithms found in the literature by means of computational simulations, and our proposal presented lower blocking probabilities with shorter computation time. Furthermore, we investigate the sensitivity and the ability of the proposed PSR to adapt itself to topological changes in the network due to both linkode addition/failure. We also investigate the behavior of the PSR in a scenario where the traffic load distribution is randomly chosen (non-uniform traffic), and we compared it to other three routing algorithms.
机译:我们提出了一种方法来设计链路成本函数,并因此提出了一种系统的形式来设计RWA算法。我们称此方法为链路成本函数设计(LCFD),它包括四个步骤:链路成本函数输入变量的选择,成本函数在一系列函数方面的扩展,总体网络性能指标的选择作为优化目标,最后,执行优化过程以找到基于离线网络仿真来优化网络性能指标的序列系数。优化过程是通过计算智能技术(粒子群优化)执行的。所提出的方法学(LCFD)用于设计自适应IA-RWA算法,我们将其称为幂级数路由(PSR)。研究了方法和IA-RWA算法的有效性。通过计算仿真,将PSR与文献中发现的其他算法进行比较,我们的建议提出了更低的阻塞概率和更短的计算时间。此外,我们研究了由于链路/节点添加/故障导致的PSR自身适应网络拓扑变化的敏感性和能力。我们还研究了在随机选择流量负载分布(非均匀流量)的情况下PSR的行为,并将其与其他三种路由算法进行了比较。

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