Cross-Layer Co-Optimization of Hollow-Core Fiber Links and Distributed Computing Workloads in AI Data Centers
Keywords:
hollow-core fiber, AI data centers, cross-layer optimization, distributed computing, optical interconnects, sustainability, governanceAbstract
Artificial intelligence data centers are becoming tightly coupled socio-technical infrastructures in which computational intensity, communication latency, energy use, and governance obligations intersect. This paper examines cross-layer co-optimization of hollow-core fiber links and distributed computing workloads in AI data centers. The central argument is that hollow-core fiber is not merely a faster physical medium; it is an architectural perturbation that can reshape topology, scheduling, synchronization, failure recovery, and sustainability decisions across the data center stack. Distributed AI workloads, including large-model training, mixture-of-experts inference, and disaggregated serving, generate bursty, low-latency-sensitive, and often collective communication patterns that challenge conventional layered design. By reducing propagation delay and nonlinear impairment, hollow-core fiber creates opportunities for flatter topologies, tighter clock synchronization, optical circuit and wavelength switching, and more aggressive workload placement. However, these benefits depend on manufacturing maturity, splicing and connector ecosystems, cost structures, repair models, and carbon accounting. The paper develops a system-level framework for cross-layer co-optimization that integrates physical-layer properties, network architecture, workload scheduling, tenant fairness, resilience, and policy. It also considers governance implications for resource allocation, carbon transparency, and equitable access. The analysis suggests that AI data centers should treat hollow-core fiber as part of a coupled design space rather than as a drop-in replacement for standard single-mode fiber. Sustainable and robust deployment will require joint optimization of optical infrastructure, workload orchestration, and institutional rules that align efficiency, fairness, and accountability.
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