Efficient Make-Before-Break Layer 2 Reoptimization

• Published in: IEEE/ACM transactions on networking Vol. 29; no. 5; pp. 1910 - 1921
• Main Authors: Duong, Huy, Jaumard, Brigitte, Coudert, David, Armolavicius, Romualdas
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.10.2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE); IEEE/ACM
• Subjects: Bandwidth; Bandwidths; Computer Science; IEEE transactions; make-before-break; Multilayers; Multiprotocol label switching; Network reconfiguration; Networking and Internet Architecture; Numerical models; Optical communication; Optimization; Reconfiguration; reoptimization; Rerouteing; rerouting; Resource management; Routing; Traffic congestion; make-before-break; rerouting; Network reconfiguration; reoptimization
• DOI: 10.1109/TNET.2021.3078581
• ISSN: 1063-6692

Optical multilayer optimization periodically reorganizes layer 0-1-2 network elements to handle both existing and dynamic traffic requirements in the most efficient manner. This delays the need for adding new resources in order to cope with the evolution of the traffic, thus saving CAPEX. The focus of this paper is on Layer 2, i.e., on capacity reoptimization at the optical transport network (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 re-defining 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. To maintain the Quality of Service, it is desirable to operate under a Make-Before-Break (MBB) paradigm, with the minimum number of reroutings. The challenge is to determine the best rerouting order 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 respect to the state of the art. We also provide some reoptimization analysis in terms of the bandwidth requirement vs. the number of reroutings.