ABSTRACT Scalability across massive network topologies is demonstrated by contemporary trunk protection methodologies, while significant inefficiencies in protection cost are exhibited by their implementations. That existing approaches unnecessarily elevate trunk protection layers well beyond operational requirements was found, and the concept of trunk graph with a cut‐resistant edge group is proposed to address the problem. Through analysis of the trunk graph's structural properties, the excess capacity inherent in current solutions can be precisely quantified. A novel category of cut‐resistant edge group configurations is identified by the breakthrough of the proposed algorithm, which enables systematic reduction of protected infrastructure elements while mandated connectivity thresholds are preserved through targeted structural modifications. To address the prohibitive computational complexity in identifying theoretically optimal cut‐resistant configurations, we have developed a fast approximation framework. It efficiently locates near‐optimal trunk graph structures with minimal preprocessing investment and substantial infrastructure savings. Our approach achieves exceptional connectivity resilience, exceeding 99.9% protection efficacy in large‐scale deployments. Trunk protection overhead is reduced by 60% compared to the state‐of‐the‐art approximation techniques under identical computational constraints. When applied to smaller network instances where optimal solutions remain computationally feasible, an average deviation of less than 1% from the theoretical minimum trunk protection requirements is maintained by our method. The gap between theoretical precision and practical implementation is successfully bridged by this innovative framework while infrastructure investment is minimized across diverse network scales.
Ma et al. (Tue,) studied this question.