Intelligent Optical Routing for Real-Time Cloud and Edge Applications
Keywords:
intelligent optical routing, cloud computing, edge computing, real-time systems, machine learning, optical switching, data center networks, sustainabilityAbstract
The convergence of cloud computing, edge computing, and real-time applications is placing unprecedented pressure on network infrastructures that were largely designed for best-effort packet transport. Intelligent optical routing has emerged as a system-level response to this pressure, combining programmable optical switching, machine learning-based control, and edge-aware resource orchestration to deliver low latency, high capacity, and predictable performance. This paper examines intelligent optical routing as a socio-technical infrastructure rather than a purely photonic engineering problem. It analyzes architectural trade-offs among hierarchical and flat topologies, electrical and optical switching, centralized and distributed control, and cloud-centric and edge-centric deployment models. The discussion emphasizes real-time constraints, robustness under failure and traffic volatility, fairness in access to optical capacity, governance of algorithmic control planes, and sustainability implications related to energy use, embodied carbon, and material life cycles. Case illustrations from data center interconnects, metro-access convergence, and edge-assisted industrial systems are used to show how optical intelligence must be coupled with policy, accountability, and operational resilience. The paper argues that future intelligent optical routing systems will succeed only if they are designed as governed infrastructures that balance performance, equity, environmental responsibility, and long-term maintainability.
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