[1] [1] WANG Y, WANG Z. Explicit routing algorithms for internet traffic engineering [C]//IEEE. Proceedings of International Conference on Computer Communications and Networks'99. Boston: IEEE, 1999: 582-588.

[2] [2] OSBORNE E D, SIMHA A. Traffic engineering with MPLS [M]. Indianapolis: Cisco Press, 2002.

[3] [3] FORTZ B, THORUP M. Optimizing OSPF/IS-IS weights in a changing world [J]. IEEE Journal on Selected Areas in Communications, 2002, 20(4):756-767.

[4] [4] HOLMBERG K, YUAN D. Optimization of internet protocol network design and routing [J]. Networks: An International Journal, 2004, 43 (1):39-53.

[5] [5] CHU J, LEA C T. Optimal link weights for ip-based networks supporting hose-model vpns[J]. IEEE/ACM Transactions on Networking, 2009, 17(3): 778-788.

[6] [6] ZHANG J, XI K, ZHANG L, et al. Optimizing network performance using weighted multipath routing[C]//IEEE. International Conference on Computer Communications and Networks'12. Munich: IEEE, 2012: 1-7.

[7] [7] CARPA R, ASSUNCAO M D, GLUCK O, et al. Evaluating the impact of SDN-induced frequent route changes on TCP flows [C]//IEEE. International Conference on Network and Service Management (CNSM). Tokyo:IEEE, 2017: 1-9.

[8] [8] ZHANG J, XI K, LUO M, et al. Dynamic hybrid routing: achieve load balancing for changing traffic demands[C]//IEEE. International Symposium on Quality of Service'14. Hong Kong: IEEE, 2014: 105-110.

[9] [9] ZHANG J, XI K, LUO M, et al. Load balancing for multiple traffic matrices using SDN hybrid routing [C]//IEEE. International Conference on High-Performance Switching and Routing'14. Vancouver: IEEE, 2014: 44-49.

[10] [10] ZHANG J, YE M, and GUO Z, et al. CFR-RL: Traffic engineering with reinforcement learning in SDN[J]. IEEE Journal on Selected Areas in Communications, 2020, 38(10): 2249-2259.

[12] [12] WILLIAMS R J. Simple statistical gradient-following algorithms for connectionist reinforcement learning [J]. Machine Learning, 1992, 8(3):229-256.

[13] [13] MNIH V, BADIA A P, MIRZA M et al. Asynchronous methods for deep reinforcement learning [C]//ICML. Proceedings of Machine Learning Research (PMLR). New York: ICML, 2016: 1928-1937.

[14] [14] ZHANG H, GOODFELLOW I, METAXAS D, et al. Self-attention generative adversarial networks [C]//ICML. International Conference on Machine Learning(PMLR). Los Angeles: ICML, 2019: 7354-7363.

[16] [16] SPRING N, MAHAJAN R, WETHERALL D. Measuring isp topologies with rocketfuel [J]. ACM SIGCOMM Computer Communication Review, 2002, 32(4):133-145.

[17] [17] ZHANG Y. ZHANG Y's abilene TM[EB/OL]. (2021-08-02)[2024-02-20]. http://www.cs.utexas. edu/~yzhang/research/AbileneTM/.

[18] [18] KODIALAM M, LAKSHMAN T, ORLIN J B, et al. Oblivious routing of highly variable traffic in service overlays and ip backbones [J]. IEEE/ACM Transactions on Networking, 2008, 17(2): 459-472.

[19] [19] VICTOR H. TMgen: traffic matrix generation tool [EB/OL]. (2020-08-10)[2024-02-20]. https://tmgen.readthedocs.io/en/latest/.

[20] [20] YE M, ZHANG J, GUO Z, et al. Date: disturbance-aware traffic engineering with reinforcement learning in software-defined networks[C]//IEEE.Proceedings of 29th International Symposium on Quality of Service (I-WQOS). Tokyo: IEEE, 2021: 1-10.