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Title: Topology design of transparent optical networks resilient to multiple node failures
Author: Barbosa, Fábio
de Sousa, Amaro
Agra, Agostinho
Keywords: Transparent optical networks
Critical node detection
Resilient network design
Issue Date: 10-Oct-2018
Publisher: IEEE
Abstract: Consider the resilience of a network defined by the average 2-terminal reliability (A2TR) against a set of critical node failures. Consider an existing transparent optical network with a total fibre length L. The first goal of this paper is to assess the resiliency gap between the existing topology and a new network topology designed to maximize its resilience with the same fibre budget L. The resiliency gap gives us a measure of how good the resilience of existing network topologies are. Consider now that an existing network is upgraded with new links aiming to maximize its resiliency improvement with a fibre budget L'. The second goal of this paper is to assess how much the resiliency gap can be reduced between a good upgraded solution and a network topology designed to maximize its resiliency with the same fibre budget L + L'. The gap reduction gives us a measure of how close to the best resilience the upgraded solutions can get for different values of L'. To reach these goals, we first describe how the Critical Node Detection problem is defined and solved in the context of transparent optical networks. Then, we propose a multi-start greedy randomized method to generate network topologies, with a given fibre length budget, that are resilient to critical node failures. This method is also adapted to the upgrade of an existing network topology. At the end, we run the proposed methods on network topologies with public available information. The computational results show that the resiliency gap of existing topologies is significantly large but network upgrades with L' = 10%L can significantly reduce the resiliency gaps provided that such upgrades are aimed at maximizing the network resilience to multiple node failures.
Peer review: yes
DOI: 10.1109/RNDM.2018.8489825
ISBN: 978-153867030-9
Publisher Version:
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