Field Trial: Demonstrating Automatic Reconfiguration of Optical Networks Based on Finite State Machine

Optical networks are evolving toward self-adaptation exploiting self-observation of network conditions (e.g., through monitoring at the physical layer). Thus, according to monitoring information, reconfiguration of network devices including switches and transponders (e.g., transmission parameters) is acted. Typically, the network is thought as centralized, where a central software defined networking (SDN) controller holds the overall view of network topology and resources and, upon connection request, it decides for routing and spectrum assignment, and, then, it configures accordingly the data plane. Similarly, the central controller receives notifications when failures occur and (re)acts by reconfiguring the data plane. However, centralized solutions can suffer from scalability and responsiveness issues, translating in delays during provisioning and recovery. In this paper, we report the demonstration in a field trial of an automatic and self-reconfigurable network. We leverage a novel control paradigm based on programmable finite state machine where each state is associated to a specific network condition and a state transition implies network reconfiguration. Thanks to this approach the central controller can instruct (pre-program) network devices making them aware of the proper reconfiguration settings associated to the network conditions. Then, the reconfiguration is triggered locally, thus increasing scalability and response speed. Two successful experiments will be shown: first, local transmission parameter adaption according to physical layer conditions; second, connection central frequency optimization mitigating filtering effects and distortions.