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Efficient Make Before Break Capacity Defragmentation

Huy Duong 1 Brigitte Jaumard 1 David Coudert 2 Ron Armolavicius 3 
2 COATI - Combinatorics, Optimization and Algorithms for Telecommunications
CRISAM - Inria Sophia Antipolis - Méditerranée , Laboratoire I3S - COMRED - COMmunications, Réseaux, systèmes Embarqués et Distribués
Abstract : Optical multilayer optimization continuously reorganizes layer 0-1-2 network elements to handle both existing and dynamic traffic requirements in the most efficient manner. This delays the need to add new resources for new requests, saving CAPEX and leads to optical network defragmentation. The focus of this paper is on Layer 2, i.e., on capacity de-fragmentation at the OTN layer when routes (e.g., LSPs in MPLS networks) are making unnecessarily long detours to evade congestion. Reconfiguration into optimized routes can be achieved by redefining the routes, one at a time, so that they use the vacant resources generated by the disappearance of services using part of a path that transits the congested section. For the Quality of Service, it is desirable to operate under Make Before Break (MBB), with the minimum number of rerouting. The challenge is to identify the rerouting order, one connection at a time, while minimizing the bandwidth requirement. We propose an exact and scalable optimization model for computing a minimum bandwidth rerouting scheme subject to MBB in the OTN layer of an optical network. Numerical results show that we can successfully apply it on networks with up to 30 nodes, a very significant improvement with the state of the art. We also provide some defragmentation analysis in terms of the bandwidth requirement vs. the number of reroutings.
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Submitted on : Thursday, November 22, 2018 - 9:55:49 AM
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Huy Duong, Brigitte Jaumard, David Coudert, Ron Armolavicius. Efficient Make Before Break Capacity Defragmentation. IEEE International Conference on High Performance Switching and Routing, Jun 2018, Bucharest, Romania. pp.6, ⟨10.1109/HPSR.2018.8850754⟩. ⟨hal-01930552⟩



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