Intelligent Resource Scheduling for Hybrid Optical-Electrical Interconnects in Cloud Computing Infrastructure
Keywords:
hybrid optical-electrical interconnects; cloud computing; resource scheduling; data center networks; optical switching; sustainability; governance; robustnessAbstract
Cloud computing infrastructure increasingly depends on interconnect fabrics that can sustain high bandwidth, low latency, and predictable energy behavior across heterogeneous workloads. Hybrid optical-electrical interconnects offer a promising architectural path because they combine the maturity, granularity, and buffering advantages of electrical switching with the bandwidth density, distance reach, and energy efficiency of optical communication. However, the coexistence of electrical and optical resources creates complex scheduling problems that cannot be reduced to conventional packet routing or virtual machine placement. This paper examines intelligent resource scheduling for hybrid optical-electrical interconnects from a system-level and socio-technical perspective. It argues that effective schedulers must coordinate workload characterization, topology awareness, optical circuit setup, electrical packet buffering, failure recovery, fairness constraints, and sustainability objectives. The analysis discusses structural trade-offs among reconfiguration latency, port count, spectrum assignment, and utilization, and it considers how machine learning and optimization-based control can operate within governance boundaries that protect tenant autonomy and network stability. The paper also explores deployment pathways, infrastructure economics, robustness under correlated failures, and policy implications for multi-tenant cloud environments. The central conclusion is that hybrid optical-electrical scheduling should be understood as an infrastructure governance problem as much as an algorithmic one. Sustainable and equitable cloud systems will require schedulers that can reason across time scales, ownership boundaries, energy sources, and service-level commitments while remaining explainable to operators, regulators, and tenants.
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This article is published under the Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
