Por favor, use este identificador para citar o enlazar este ítem:https://uvadoc.uva.es/handle/10324/62310
Título
Performance Evaluation of TI-LFA in Traffic-Engineered Segment Routing-Based Networks
Autor
Congreso
2023 19th International Conference on the Design of Reliable Communication Networks (DRCN),
Año del Documento
2023
Editorial
Institute of Electrical and Electronics Engineers (IEEE)
Descripción Física
8 p.
Descripción
Producción Científica
Documento Fuente
2023 19th International Conference on the Design of Reliable Communication Networks (DRCN), Vilanova i la Geltru, Spain, 2023, pp. 1-8
Abstract
Link failures have a significant negative impact on the availability of a network and should therefore be resolved as soon as possible. Because of the slow convergence time of routing protocols upon detection of a link failure, several IP Fast ReRoute (FRR) mechanisms have been developed to overcome this problem. Recently, segment routing, which is a flexible and scalable way of doing source routing, enabled a new FRR mechanism called Topology Independent Loop-Free Alternate (TI-LFA). As the name suggests, the key feature of TI-LFA is that it guarantees a loop-free detour against any link failure in any network topology. However, typically fast responses to failures only aim to restore the loop-free connection between the affected routers and do not consider the resulting delay or impact on network congestion. This paper presents an initial study on the selected TI-LFA backup paths and their effect on the overall network performance. By means of simulation, we evaluate how efficient TI-LFA reroutes traffic for a number of traffic engineering approaches. Our results quantify the impact of different traffic engineering approaches and network loads on the performance of TI-LFA. This suggests potential directions for improving the effectiveness of TI-LFA protection in segment routing.
Palabras Clave
Performance evaluation
Network topology
Routing
Reliability engineering
Routing protocols
Topology
Delays
Patrocinador
EU H2020 MSCA ITN-ETN IoTalentum (grant no. 953442)
EU H2020-ICT-52-2020 TeraFlow Project (grant 101015857)
Ministerio de Ciencia e Innovación y Agencia Estatal de Investigación (Proyecto PID2020-112675RB-C42 financiado por MCIN/AEI/10.13039/501100011033)
EU H2020-ICT-52-2020 TeraFlow Project (grant 101015857)
Ministerio de Ciencia e Innovación y Agencia Estatal de Investigación (Proyecto PID2020-112675RB-C42 financiado por MCIN/AEI/10.13039/501100011033)
Version del Editor
Idioma
eng
Tipo de versión
info:eu-repo/semantics/acceptedVersion
Derechos
openAccess
Collections
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