Research on Joint Scheduling Method of Heterogeneous TT&C Network Resources Based on Improved DQN Algorithm
Naiyang Xue, Dan Ding, Yile Fan, Zhiqiang Wang · 2021 IEEE 2nd International Conference on Information Technology, Big Data and Artificial Intelligence (ICIBA) · 2021
Aiming at the joint scheduling problem of heterogeneous TT&C network resources, a suitable model is established and solved by artificial intelligence algorithms. Construct a heterogeneous TT&C network resource scheduling model based on the characteristics of state-owned and commercial TT&C resources and the preference of TT&C resources, and use the improved DQN algorithm to solve the problem, and perform resource scheduling experiments under a certain scale scenario to obtain the optimal heterogeneous TT&C resource combination scheduling plan. The simulation results show that the designed improved DQN algorithm can effectively solve the joint scheduling optimization problem of heterogeneous TT&C resources.