Optimized FlexEthernet for Inter-Domain Traffic Restoration

Abstract

Restoring traffic in multi-layer multi-domain networks (MLMD) can be inefficient and expensive due to the reconfiguration of both intra-domain and inter-domain paths under limited resources and information sharing. This often results in traffic loss and resource over-provisioning within the MLMD, leading to sub-optimal restoration throughput and high costs. In this study, we harness FlexEthernet (FlexE) on inter-domain links to maximize the restoration throughput at minimum cost. FlexE link aggregation is an effective technique to deal with the costly impact of alternative domain rerouting that allows diverting traffic over aggregated links parallel to the failed ones, without disrupting the intra-domain connections. Additionally, FlexE helps increase network reutilization by leveraging time division multiplexing (TDM) to flexibly shift affected traffic to underutilized aggregated links. However, scheduling traffic migration in FlexE is a challenging issue that has not been fully investigated in the literature. In this paper, we initially formulate the FlexE-based traffic restoration problem as a mixed integer non-linear program (MINLP) and then introduce an approximation algorithm to efficiently solve this problem in polynomial time. Furthermore, we propose a supervised learning approach to predict the optimal restoration policy for large-size instances. Experimental results show that our solution restores up to 14% more traffic than a state-of-the-art approach.