First experimental assessment of ABNO-driven in-operation flexgrid network re-optimization
Traffic affected by link failures can be recovered using path restoration schemes. In dynamically operated networks provided with a control plane, restoration algorithms run in a centralized element, such as the path computation element (PCE). To increase traffic restorability in flexgrid networks,...
| Autores: | , , , , , , |
|---|---|
| Tipo de recurso: | artículo |
| Fecha de publicación: | 2015 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/77844 |
| Acceso en línea: | https://hdl.handle.net/2117/77844 https://dx.doi.org/10.1109/JLT.2014.2343157 |
| Access Level: | acceso abierto |
| Palabra clave: | Optical fibers Heuristic programming Flexgrid planning In-operation planning Network experiments Optical networks Fibres òptiques Programació heurística Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Telecomunicació òptica::Fibra òptica |
| Sumario: | Traffic affected by link failures can be recovered using path restoration schemes. In dynamically operated networks provided with a control plane, restoration algorithms run in a centralized element, such as the path computation element (PCE). To increase traffic restorability in flexgrid networks, multiple paths, subconnections, can be used to restore every single affected connection. However, the multipath restoration scheme might result in a poor resource utilization entailing a lesser grade of service. In-operation network planning algorithms can be used to mitigate this problem once the failed link is repaired; we propose solving the so-called multipath after failure repair optimization problem (MP-AFRO) to reduce subconnections count by aggregating those belonging to the same original connection and rerouting the resulting connection to release spectral resources. The MP-AFRO problem is modeled using a mixed integer linear program formulation. In view of the complexity of the model and the limited time to solve the problem, we propose a heuristic algorithm that provides a good tradeoff between complexity and optimality. The performance on the MP-AFRO heuristic is firstly validated by simulation. Next, the heuristic algorithm is deployed inside an in-operation planning tool in the form of back-end PCE (bPCE) inside the application-based network operations architecture controlling a network; the bPCE is connected to the centralized active stateful PCE. MP-AFRO is experimentally demonstrated using a distributed field trial test-bed connecting the premises of Telefonica (Madrid), CNIT (Pisa), and UPC (Barcelona). |
|---|