[1] [1] You X, Wang C X, Huang J, et al. Towards 6G wireless communication networks: vision, enabling technologies, and new paradigm shifts [J]. Science China Information Sciences, 2021, 64: 110301.

[3] [3] Linguaglossa L, Lange S, Pontarelli S, et al. Survey of performance acceleration techniques for network function virtualization [J]. Proceedings of the IEEE, 2019, 107(4): 746-764.

[5] [5] Chen H, Wang S, Li G, et al. Distributed orchestration of service function chains for edge intelligence in the industrial internet of things [J]. IEEE Trans. on Industrial Informatics, 2021, 18(9): 6244-6254.

[6] [6] Ding L, Lin Z, Shi X, et al. Target-value-competition-based multi-agent deep reinforcement learning algorithm for distributed nonconvex economic dispatch [J]. IEEE Trans. on Power Systems, 2022, 38(1): 204-217.

[7] [7] Sun P, Lan J, Li J, et al. Combining deep reinforcement learning with graph neural networks for optimal VNF placement [J]. IEEE Communications Letters, 2020, 25(1): 176-180.

[8] [8] Chen Z, Li H, Ota K, et al. Deep reinforcement learning for AoI aware VNF placement in multiple source systems [C]// 2022 IEEE Global Communications Conference, 2022: 2873-2878.

[9] [9] Bunyakitanon M, Vasilakos X, Nejabati R, et al. End-to-end performance-based autonomous VNF placement with adopted reinforcement learning [J]. IEEE Trans. on Cognitive Communications and Networking, 2020, 6(2): 534-547.

[10] [10] Pei J, Hong P, Pan M, et al. Optimal VNF placement via deep reinforcement learning in SDN/NFV-enabled networks [J]. IEEE J. on Sel. Areas in Communications, 2019, 38(2): 263-278.

[11] [11] Wang S, Yuen C, Ni W, et al. Multiagent deep reinforcement learning for cost-and-delay-sensitive virtual network function placement and routing [J]. IEEE Trans. on Communications, 2022, 70(8): 5208-5224.

[12] [12] Tan X, Zhou L, Wang H, et al. Cooperative multi-agent reinforcement-learning-based distributed dynamic spectrum access in cognitive radio networks [J]. IEEE Internet of Things J., 2022, 9(19): 19477-19488.

[13] [13] Chen Z, Hu J, Min G, et al. Adaptive and efficient resource allocation in cloud datacenters using actor-critic deep reinforcement learning [J]. IEEE Trans. on Parallel and Distributed Systems, 2021, 33(8): 1911-1923.

[14] [14] Cui Y, Huang X, He P, et al. QoS guaranteed network slicing orchestration for internet of vehicles [J]. IEEE Internet of Things J., 2022, 9(16): 15215-15227.

[15] [15] Gu L, Zeng D, Li W, et al. Intelligent VNF orchestration and flow scheduling via model-assisted deep reinforcement learning [J]. IEEE J. on Sel. Areas in Communications, 2019, 38(2): 279-291.