下一代无线网络必须在突发且严重的干扰下维持可靠运行，尤其在超可靠低时延通信（URLLC）场景中，严格的时延约束主导系统设计。本文从时间中心视角出发，通过显式引入有限码长（FBL）通信，将传输时长建模为一种可控资源，以支持系统恢复，从而应对网络韧性问题。为此，我们提出一种统一的跨层框架，联合耦合队列动态、速率自适应与码长优化，使系统能够主动吸收、适应并恢复各类韧性事件。为系统性评估上述机制，我们引入一种可解释的韧性度量，将干扰影响分解为吸收损失、适应效率与恢复行为三部分，从而实现对系统韧性直接且直观的评估。基于该框架，我们设计了一种三阶段交替优化方法，联合优化物理层参数（包括波束赋形、可重构智能表面（RIS）相位偏移及码长），揭示了FBL体制下时延感知资源分配的重要性。数值结果表明，所提方法在重复信道中断与AI驱动的业务激增场景下均展现出优异的韧性性能，验证了跨层资源自适应的有效性。最后，所提出的韧性度量支持在不同方法与干扰类型间进行直观、一致的韧性性能比较，并揭示各自的优势与局限。

Next-generation wireless networks must maintain reliable operation under abrupt and severe disruptions, particularly in ultra-reliable low-latency communication (URLLC) scenarios where strict time constraints dominate system design. This work addresses network resilience from a time-centric perspective by explicitly integrating finite blocklength (FBL) communication, thereby exposing transmission duration as a controllable resource for system recovery. To this end, we propose a unified cross-layer framework that jointly couples queue dynamics, rate adaptation, and blocklength optimization, enabling the system to actively absorb, adapt to, and recover from diverse resilience events. To systematically evaluate these mechanisms, we introduce an interpretable resilience metric that decomposes disruption impact into absorption loss, adaptation efficiency, and recovery behavior, enabling a direct and intuitive assessment of system resilience. Building on this framework, we develop a three-stage alternating optimization approach that jointly optimizes PHY-layer parameters, including beamforming, reconfigurable intelligent surface (RIS) phase shifts, and blocklength, revealing the importance of time-aware resource allocation in the FBL regime. Numerical results demonstrate strong resilience performance under repeated channel disruptions and AI-driven traffic surges, highlighting the effectiveness of cross-layer resource adaptation. Finally, the proposed resilience metric enables an intuitive and consistent comparison of resilience performance across different approaches and disruption types, while revealing their respective strengths and limitations.