Low-Latency Optical Interconnect Design for Real-Time Distributed Edge Intelligence and Cloud Collaboration
Keywords:
optical interconnects; edge intelligence; cloud collaboration; low latency; hollow-core fiber; distributed systems; synchronization; resilience; sustainability; governanceAbstract
The rapid expansion of real-time artificial intelligence services has created a structural tension between centralized cloud computation and latency-sensitive edge environments. Distributed edge intelligence promises localized inference, privacy preservation, and rapid control loops, yet many advanced models still require cloud-scale training, orchestration, and data aggregation. Optical interconnects are increasingly positioned as the physical substrate that can reconcile these competing demands by offering high bandwidth, low propagation delay, and deterministic synchronization across edge, access, and cloud domains. This paper examines the system-level design of low-latency optical interconnects for real-time distributed edge intelligence and cloud collaboration. It analyzes architectural choices across wavelength switching, hollow-core fiber, silicon photonics, optical circuit switching, space-division multiplexing, and software-defined control planes. The discussion emphasizes trade-offs among latency, jitter, energy consumption, scalability, deployment cost, and operational resilience. It also considers governance, fairness, policy, and sustainability implications that arise when optical infrastructure becomes a shared socio-technical resource. Through cross-domain cases in manufacturing, mobility, telehealth, and immersive collaboration, the paper shows that optical interconnect design cannot be reduced to component optimization. Rather, it must be treated as an integrative infrastructure problem involving synchronization, scheduling, multi-tenant fairness, fault tolerance, and public accountability. The paper concludes with a forward-looking research agenda that joins photonic engineering with distributed systems, AI orchestration, and infrastructure governance.
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