An effective hybrid V2V/V2I transmission latency method based on LSTM neural network

Gui, 2020, 6G: opening new horizons for integration of comfort, security and intelligence, IEEE Wirel. Commun., 27, 126, 10.1109/MWC.001.1900516 Lai, 2021, Intelligent secure mobile edge computing for beyond 5G wireless networks, Phys. Commun., 45, 1 Sun, 2020, Surveillance plane aided air-ground integrated vehicular networks: Architectures, applications, and potential, IEEE Wirel. Commun., 27, 122, 10.1109/MWC.001.2000079 Guo, 2021, Efficient and flexible management for industrial internet of things: A federated learning approach, Comput. Netw., 192, 1, 10.1016/j.comnet.2021.108122 Sun, 2021, Aviation data lake: Using side information to enhance future air-ground vehicle networks, IEEE Veh. Technol. Mag., 16, 40, 10.1109/MVT.2020.3014598 Xia, 2019, Secure cache-aided multi-relay networks in the presence of multiple eavesdroppers, IEEE Trans. Commun., 67, 7672, 10.1109/TCOMM.2019.2935047 Zhen, 2021, Early collision detection for massive random access in satellite-based internet of things, IEEE Trans. Veh. Technol., 70, 5184, 10.1109/TVT.2021.3076015 Tang, 2021, Battery-constrained federated edge learning in UAV-enabled IoT for B5G/6G networks, Phys. Commun., 47, 1, 10.1016/j.phycom.2021.101381 Hu, 2021, UAV-assisted vehicular edge computing for the 6G internet of vehicles: Architecture, intelligence, and challenges, IEEE Commun. Stand. Mag., 5, 12, 10.1109/MCOMSTD.001.2000017 Qureshi, 2021, Internet of vehicles: Key technologies, network model, solutions and challenges with future aspects, IEEE Trans. Intell. Transp. Syst., 22, 1777, 10.1109/TITS.2020.2994972 Alladi, 2021, Artificial intelligence (AI)-empowered intrusion detection architecture for the internet of vehicles, IEEE Wirel. Commun., 28, 144, 10.1109/MWC.001.2000428 Vegni, 2011, Hybrid vehicular communications based on V2V-V2I protocol switching, Int. J. Veh. Inf. Commun. Syst., 2, 213 Chen, 2021, Physical-layer security on mobile edge computing for emerging cyber physical systems, Comput. Commun., 178, 297 Sharma nad H. Liu, 2021, A machine-learning-based data-centric misbehavior detection model for internet of vehicles, IEEE Internet Things J., 8, 4991, 10.1109/JIOT.2020.3035035 Pokhrel, 2021, Software defined internet of vehicles for automation and orchestration, IEEE Trans. Intell. Transp. Syst., 22, 3890, 10.1109/TITS.2021.3077363 Zhou, 2021, Pso based offloading strategy for cache-enabled mobile edge computing UAV networks, Cluster Comput., 2021, 1 Chen, 2021, Intelligent ubiquitous computing for future UAV-enabled MEC network systems, Cluster Comput., 2021, 1 Kreutz, 2015, Software-defined networking: A comprehensive survey, Proc. IEEE, 103, 14, 10.1109/JPROC.2014.2371999 He, 2016, A novel load balancing strategy of software-defined cloud/fog networking in the internet of vehicles, China Commun., 13, 140, 10.1109/CC.2016.7405730 Wang, 2017, An SDN-based collaborative transmission algorithm for the internet of vehicles, Comput. Appl. Softw., 34, 166 Tang, 2021, Comprehensive survey on machine learning in vehicular network: Technology, applications and challenges, IEEE Commun. Surv. Tutor., 23, 2027, 10.1109/COMST.2021.3089688 Wang, 2021, An adaptive deep learning-based UAV receiver design for coded MIMO with correlated noise, Phys. Commun., 45, 1 Li, 2021, Dynamic offloading for multiuser Muti-CAP MEC networks: A deep reinforcement learning approach, IEEE Trans. Veh. Technol., 70, 2922, 10.1109/TVT.2021.3058995 Zhang, 2020 Zhu, 2015, On stochastic analysis of greedy routing in vehicular networks, IEEE Trans. Intell. Transp. Syst., 16, 3353, 10.1109/TITS.2015.2446771 Gu, 2015 Chen, 2017, Vehicle-to-everything (V2X) service supported by LTE-based systems and 5G, IEEE Commun. Stand. Mag., 1, 70, 10.1109/MCOMSTD.2017.1700015 Zhao, 2019, Hybrid anonymous channel for recipient untraceability via SDN-based node obfuscation scheme, J. Commun., 40, 55 A. Huang, N. Nikaein, et al. Low latency MEC framework for SDN-based LTE/LTE-A networks, in: IEEE International Conference on Communications, ICC, Paris, France, 21–25 May 2017, 2017, pp. 1–6. Ling, 2021, An intelligent traffic oriented traffic estimation method for internet of vehicles network, J. Xidian Univ., 48, 40 Feng, 2020, Attribute-based encryption with parallel outsourced decryption for edge intelligent IoV, IEEE Trans. Veh. Technol., 69, 13784, 10.1109/TVT.2020.3027568 Yang, 2021, Simulation of non-homogeneous Poisson process of customer arrival in three-dimensional garage, J. Shengzhen Univ., 1991, 205 Li, 2021, A non-aligned Poisson process model for accident prediction, J. Xi’an Univ. Archit. Technol., 38, 121 He, 2021, Learning based signal detection for MIMO systems with unknown noise statistics, IEEE Trans. Commun., 69, 3025, 10.1109/TCOMM.2021.3058999 Wang, 2021, Federated learning for automatic modulation classification under class imbalance and varying noise condition, IEEE Trans. Cogn. Commun. Netw. Wang, 2021, Compressive sampled CSI feedback method based on deep learning for FDD massive MIMO systems, IEEE Trans. Commun., 69, 5873, 10.1109/TCOMM.2021.3086525 He, 2021, Edge device identification based on federated learning and network traffic feature engineering, IEEE Trans. Cogn. Commun. Netw. Zeng, 2021, Downlink CSI feedback algorithm with deep transfer learning for FDD massive MIMO systems, IEEE Trans. Cogn. Commun. Netw., 10.1109/TCCN.2021.3084409 Tu, 2021, Large-scale real-world radio signal recognition with deep learning, Chin. J. Aeronaut. Wang, 2021, An efficient specific emitter identification method based on complex-valued neural networks and network compression, IEEE J. Sel. Areas Commun., 39, 2305, 10.1109/JSAC.2021.3087243 Wang, 2021, Multi-task learning for generalized automatic modulation classification under non-Gaussian noise with varying SNR conditions, IEEE Trans. Wireless Commun., 20, 3587, 10.1109/TWC.2021.3052222 Ren, 2021, Short-term traffic flow prediction: A method of combined deep learnings, J. Adv. Transp., 722, 1 Yu, 2021, Deep learning-based traffic safety solution for a mixture of autonomous and manual vehicles in a 5G-enabled intelligent transportation system, IEEE Trans. Intell. Transp. Syst., 22, 4337, 10.1109/TITS.2020.3042504 Mou, 2019, T-LSTM: A long short-term memory neural network enhanced by temporal information for traffic flow prediction, IEEE Access, 7, 98053, 10.1109/ACCESS.2019.2929692 Kochar, 1996, Some results on interarrival times of nonhomogeneous Poisson processes, Probab. Engrg. Inform. Sci., 10, 75, 10.1017/S0269964800004186 Tang, 2019, Delay-minimization routing for heterogeneous VANETs with machine learning based mobility prediction, IEEE Trans. Veh. Technol., 68, 3967, 10.1109/TVT.2019.2899627 Tang, 2022, Computational intelligence and deep learning for next-generation edge-enabled industrial IoT, IEEE Trans. Netw. Sci. Eng., 1