Joint optimization of reconfiguration and traffic planning in time‐triggered networks

Abstract

AbstractThe existing research on time‐triggered network reconfiguration neglects redundant traffic states, posing a challenge in effectively balancing traffic performance and reconfiguration efficiency in practical deployments. In response to these limitations, a novel joint optimization approach is introduced for reconfiguration and traffic planning. Initially, the efficiency of reconfiguration solutions is enhanced by sacrificing the delay performance of redundant flows and prioritizing compressed yet tailored constraints. Subsequently, a tabu‐based optimization algorithm is employed to provide more flexible enhancements to the delay performance of network‐wide traffic. The outcomes demonstrate that the proposed method significantly outperforms incremental reconfiguration, improving the solution efficiency of the reconfiguration recovery phase by over 75.38%. Furthermore, through multiple rounds of reconfiguration, the approach achieves an 8.38% improvement in the average delay performance of all flows, even with redundant flows sacrificed.