Resource Allocation in Multicore Elastic Optical Networks: A Deep Reinforcement Learning Approach. (arXiv:2207.02074v1 [cs.LG])

A deep reinforcement learning approach is applied, for the first time, to
solve the routing, modulation, spectrum and core allocation (RMSCA) problem in
dynamic multicore fiber elastic optical networks (MCF-EONs). To do so, a new
environment - compatible with OpenAI's Gym - was designed and implemented to
emulate the operation of MCF-EONs. The new environment processes the agent
actions (selection of route, core and spectrum slot) by considering the network
state and physical-layer-related aspects. The latter includes the available
modulation …

arxiv learning lg multicore networks reinforcement reinforcement learning