Reinforcement Learning-Based Routing and Resource Allocation in Clock-Synchronized Optical Data Center Networks
Keywords:
optical data center networks; clock synchronization; reinforcement learning; routing; resource allocation; hollow-core fiber; socio-technical governance; sustainability; network fairnessAbstract
Optical data center networks are increasingly positioned as the interconnection substrate for artificial intelligence training, latency-sensitive cloud services, and large-scale distributed storage. When optical switching is combined with precise clock synchronization, the network can exploit deterministic time slices, wavelength-level reconfiguration, and low-jitter forwarding to achieve performance levels difficult to match with conventional electrical packet switching alone. This paper examines reinforcement learning-based routing and resource allocation in clock-synchronized optical data center networks from a system-level perspective. It argues that the central design problem is not merely algorithmic optimization but the alignment of learning policies with physical synchronization, switching granularity, failure semantics, multi-tenant fairness, energy constraints, and governance requirements. The analysis first reviews the architectural foundations of clock-synchronized optical fabrics, including wavelength switching, hollow-core fiber, centralized scheduling, and synchronization domains. It then develops a conceptual reinforcement learning framework for routing and resource allocation, emphasizing state representation, reward design, multi-agent coordination, safety constraints, and sim-to-real transfer. The paper further evaluates structural trade-offs involving robustness, interpretability, sustainability, and equitable resource distribution. It also discusses deployment pathways, policy implications, and cross-domain lessons from power grids, aviation, and software-defined networking. The conclusion is that reinforcement learning can improve adaptability and utilization in clock-synchronized optical data centers, but only when embedded within a governance architecture that treats synchronization, safety, fairness, and energy as first-class operational constraints rather than post hoc corrections.
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