Optimal Control Method for Congestion Control and Delay Reduction in Deterministic Networks

The proliferation of the types and number of the beyond fifth generation / the six generation (B5G/6G) network services will contribute to severe network congestion collapse, which is detrimental to deterministic service assurance for time-sensitive businesses. Faced with the congestion control problem in deterministic networks, the regulation and control effect of network macroscopic congestion state on the node various microscopic control strategies should be sufficiently considered from a global view. In this paper, a congestion control system model is constructed, which includes node-level congestion states and control strategies and network-level optimization objective. Continuous congestion state transition and real-time control strategy selection are analyzed to minimize the network delay and congestion degree with the lowest control cost. The analytical solution to optimal control strategy is derived based on the optimal control theory, and the numerical solution is analyzed by proposing a congestion control discretization algorithm (CCDA). Simulation results demonstrate that the congestion degree of each network node gradually decreases with the obtained CCDA strategies. The impacts of model parameters such as congestion deterioration probability and delay weight coefficients on the evolution of network total loss and optimal strategies are also analyzed. Moreover, the network total loss of the proposed congestion control model is lower than the baseline model, which can provide effective and referable theoretical guidance for congestion control problem in deterministic networks.