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Topological optimization for spare-sharing-based wavelength-routed all-optical networks

机译:基于备用共享的波长路由全光网络的拓扑优化

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In this paper, we propose a two-level fault tolerance strategy for wavelength-routed all-optical networks. The first-level strategy is applied to handle the large-scale disaster induced failures while the second-level strategy protects the network against regular single-link failures. The first-level fault tolerance is achieved by solving a topological optimization problem to re-regulate the traffic away from the disaster-affected area with minimum resource cost. Shared lightpath protection is applied in the second-level fault tolerance design to reduce resource allocation. First, by comparing with a simple greedy approach that we develop, we show that the traditional Routing and Wavelength Assignment (RWA) method, in which the routing and wavelength assignment are considered in a separate fashion, cannot lead to satisfying performance. Next, in order to obtain better performance, based on drawback analysis of the greedy approach, we propose a two-phase heuristic algorithm, in which the first phase is designed to generate an initial feasible solution and the second phase iteratively perfects the initial solution until no improvement can be made. For the design of the first phase, two variations are proposed featuring different types of initial solution generation. The numerical results show that, combined with perfection phase, both design variations can lead to considerable performance improvement over the greedy solutions. Finally, we propose a Performance Indicator (PI) that provides insight into the reason for performance difference among algorithms.
机译:在本文中,我们提出了一种用于波长路由全光网络的二级容错策略。第一级策略用于处理大规模的灾难性故障,而第二级策略则保护网络免受常规单链路故障的影响。通过解决拓扑优化问题,以最小的资源成本重新调整远离受灾地区的流量,可以实现第一级的容错能力。二级容错设计中采用了共享光路保护,以减少资源分配。首先,通过与我们开发的简单贪婪方法进行比较,我们表明,传统的路由和波长分配(RWA)方法(以单独的方式考虑路由和波长分配)无法带来令人满意的性能。接下来,为了获得更好的性能,基于贪婪方法的缺陷分析,我们提出了一种两阶段启发式算法,其中第一阶段被设计为生成初始可行解,第二阶段迭代地完善初始解直到无法改善。对于第一阶段的设计,提出了两种变体,它们具有不同类型的初始解决方案生成。数值结果表明,与完善阶段相结合,这两种设计变化都可以带来比贪婪解决方案可观的性能改进。最后,我们提出了一个性能指标(PI),可以深入了解算法之间性能差异的原因。

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