Multi-Objective Optimization of Latency, Energy Consumption, and Reliability in Optical Switching Networks

Abstract

Optical switching networks have become a foundational infrastructure for data centers, high-performance computing, telecommunications, and increasingly for distributed artificial intelligence systems. Their design must satisfy competing objectives: minimizing latency, reducing energy consumption, and preserving reliability under dynamic and uncertain traffic conditions. This paper examines multi-objective optimization of latency, energy consumption, and reliability in optical switching networks from a system-level perspective. It argues that these objectives are not independent technical variables but are structurally coupled through switching granularity, control-plane design, hardware redundancy, fiber topology, cooling requirements, and operational governance. The analysis compares circuit switching, wavelength switching, burst switching, packet switching, and hybrid electrical-optical architectures, showing how each paradigm distributes latency and energy burdens differently across the network stack. It then reviews multi-objective optimization approaches, including Pareto-based evolutionary methods, simulation-driven design, and software-defined orchestration, while emphasizing that optimization outcomes are shaped by institutional priorities and deployment constraints. The paper further discusses sustainability, robustness, fairness, and policy implications, noting that energy-efficient designs can either improve or worsen reliability depending on maintenance regimes, traffic fairness, and failure recovery strategies. Case illustrations from intra-data center interconnect, cloud infrastructure, and resilient backbone networks clarify the trade-offs. The conclusion proposes that future optical switching systems should be evaluated as socio-technical infrastructures rather than purely technical artifacts, with optimization frameworks that incorporate lifecycle energy, service equity, failure transparency, and adaptive governance.