Performance Evaluation of Cloud-native Wavelength Conversion in Disaggregated Optical Networks

In SDN-enabled disaggregated optical networks, switches and wavelength converters are managed through software abstractions that model their capabilities, enabling greater flexibility and improved performance. While traditional approaches statically assign converters to specific nodes, such abstractions allow wavelength conversion to be considered as a distributed processing function, dynamically migrating across the network like a Cloud-based service. This enhances the ability of the control layer to flexibly allocate conversion resources to reduce blocking occurrences. Additionally, the orchestration layer dynamically selects wavelength allocation policies based on these abstractions, ensuring an optimal balance between performance and resource efficiency. This paper proposes a novel Cloud-native approach to wavelength conversion in disaggregated optical networks. We present a framework for orchestrating and controlling end-to-end services with a focus on lightpath provisioning, supported by a resource availability model that facilitates efficient wavelength selection. Our evaluation compares multiple wavelength assignment algorithms through both static and dynamic simulations. The results highlight key trade-offs among these algorithms in terms of blocking probability, resource utilization, and overall cost efficiency, providing valuable insights for improving the overall network performance.