Metaheuristic optimization of end‐to‐end service routing in multidomain network architectures

Abstract As we move toward the era of 6G networks, the emergence of numerous end‐to‐end services with diverse user demands is anticipated. To support these services under varying network conditions, traffic must be routed through optimal paths that satisfy quality of service (QoS) requirements while minimizing transmission costs. Furthermore, climate change concerns are increasing pressure to reduce both energy consumption and carbon emissions resulting from service operations. Given that these complex factors affect multiple domains, it is essential to develop an effective method for routing optimization. To address this issue, we propose a metaheuristic optimization method for end‐to‐end service routing that considers dynamic network metrics and computing site information to reduce energy consumption and carbon emissions. Evaluation results show that our approach selects near‐optimal paths by accounting for various factors, including QoS, energy consumption, and carbon emissions. Compared with benchmark schemes, our model reduces the joint energy and carbon objective by up to 63%, average service latency by up to 75%, and maintains the highest availability across all scenarios.