
info@juzhikan.asia
Nanjing Guorui Defense Systems Co., Ltd.Jiangsu Nanjing, 210000;
Abstract:Aiming at the sensitive problem of the delay in the construction of the cross-domain connection between the terminal device and the remote server in the future large-scale machine communication, a deep sequence learning routing technology is proposed. This technology breaks through the basic setting of traditional routing calculations based on topology information, makes full use of the implicit correlation between historical routing and topology, and constructs a deep neural network to achieve the mapping of routing requests and routing results in a given network state. Experimental results show that the trained neural network can adaptively generate routing results based on routing requests, without the need for multi-domain collaborative calculations, and reducing the road construction delay by about 50%.
Keywords:cross-domain connection, delay, deep neural network, sequence learning routing
References
[1]D. Liu, B. Chen, C. Yang, et al., “Caching at the wireless edge: design aspects, challenges, and future directions,” IEEE Communications Magazine, 54(9): 22-28, 2016.
[2]K. Shanmugam, N. Golrezaei, A. G. Dimakis, et al., “Femtocaching: Wireless content delivery through distributed caching helpers,” IEEE Transactions on Information Theory, 59(12): 8402-8413, 2013.
[3]N. Karamchandani, U. Niesen, M. A. Maddah-Ali, et al., “Hierarchical coded caching,” IEEE Transactions on Information Theory, 62(6): 3212-3229, 2016.
[4]Y. Guo, L. Duan and R. Zhang, “Cooperative local caching under heterogeneous file preferences,” IEEE Transactions on Communications, 65(1): 444-457, 2017.
[5]M. Ji, G. Caire and A. F. Molisch, “Wireless device-to-device caching networks: Basic principles and system performance,” IEEE Journal on Selected Areas in Communications, 34(1): 176-189, 2016.
[6]S. Zhang, N. Zhang, P. Yang, et al., “Cost-effective cache deployment in mobile heterogeneous networks,” IEEE Transactions on Vehicular Technology, 66(12): 11264-11276, 2017.
[7]M. Z. Win, W. Dai, Y. Shen, et al., “Network Operation Strategies for Efficient Localization and Navigation,” Proceedings of the IEEE, 106(7): 1224-1254, 2018.
[8]M. Z. Win, Y. Shen and W. Dai, “A Theoretical Foundation of Network Localization and Navigation,” Proceedings of the IEEE, 106(7): 1136-116, 2018.
[9]P. P. Ray, M. Mukherjee and L. Shu, “Internet of things for disaster management: State-of-the-art and prospects,” IEEE Access, 5(1): 18818-1883, 2017.