[1] Wang C,Liang C,Yu F R,et al.Computation offloading and resource allocation in wireless cellular networks with mobile edge computing[J].IEEE Transactions on Wireless Communications,2017,16(8):4924-4938.
[2] Haber E E,Nguyen T M,Assi C.Joint optimization of computational cost and devices energy for task offloading in multi-tier edge-clouds[J].IEEE Transactions on Communications,2019,67(5):3407-3421.
[3] Chen S,Zheng Y,Lu W,et al.Energy-optimal dynamic computation offloading for industrial IoT in fog computing[J].IEEE Transactions on Green Communications and Networking,2019,DOI:10.1109/TGCN.2019.2960767.
[4] Chen S,Zheng Y,Wang K,et al.Delay guaranteed energy-efficient computation offloading for industrial IoT in fog computing[A].Proceedings of IEEE International Conference on Communications (ICC)[C].Shanghai,China:IEEE,2019.1-6.
[5] Lei L,Xu H,Xiong X,et al.Joint computation offloading and multiuser scheduling using approximate dynamic programming in NB-IoT edge computing system[J].IEEE Internet of Things Journal,2019,6(3):5345-5362.
[6] Chen S,Zhu X,Zhang H,et al.Efficient privacy preserving data collection and computation offloading for fog-assisted IoT[J].IEEE Transactions on Sustainable Computing,2020,DOI:10.1109/TSUSC.2020.2968589.
[7] Yu S,Wang X,Langar R.Computation offloading for mobile edge computing:a deep learning approach[A].Proceedings of IEEE International Symposium on Personal,Indoor and Mobile Radio Communications (PIMRC)[C].Montreal,Canada:IEEE,2017.1-6.
[8] Li L,Ota K,Dong M.Deep learning for smart industry:efficient manufacture inspection system with fog computing[J].IEEE Transactions on Industrial Informatics,2018,14(10):4665-4673.
[9] Zhu X,Chen S,Chen S,et al.Energy and delay co-aware computation offloading with deep learning in fog computing networks[A].Proceedings of IEEE International Performance Computing and Communications Conference (IPCCC)[C].London,UK:IEEE,2019.1-6.
[10] Dab B,Aitsaadi N,Langar R.Q-learning algorithm for joint computation offloading and resource allocation in edge cloud[A].Proceedings of IFIP/IEEE Symposium on Integrated Network and Service Management (IM)[C].Arlington,USA:IEEE,2019.8-12.
[11] Liu X,Qin Z,Gao Y.Resource allocation for edge computing in IoT networks via reinforcement learning[A].Proceedings of IEEE International Conference on Communications (ICC)[C].Shanghai,China:IEEE,2019.20-24.
[12] Huang L,Feng X,Qian L,et al.Deep reinforcement learning-based task offloading and resource allocation for mobile edge computing[A].Proceedings of International Conference on Machine Learning and Intelligent Communications (MLICOM)[C].Nanjing,China:Springer Verlag,2018.33-42.
[13] Meng H,Chao D,Huo R,et al.Deep reinforcement learning based delay-sensitive task scheduling and resource management algorithm for multi-user mobile-edge computing systems[A].Proceedings of International Conference on Mathematics and Artificial Intelligence (ICMAI)[C].Chengdu,China:ACM,2019.66-70.
[14] Wei Y,Yu F R,Song M,et al.Joint optimization of caching,computing,and radio resources for fog-enabled IoT using natural actor-critic deep reinforcement learning[J].IEEE Internet of Things Journal,2019,6(2):2061-2073.
[15] Chen X,Zhang H,Wu C,et al.Performance optimization in mobile-edge computing via deep reinforcement learning[A].Proceedings of IEEE Vehicular Technology Conference (VTC-Fall)[C].Chicago,USA:IEEE,2018.27-30.
[16] Huang L,Bi S,Zhang Y J.Deep reinforcement learning for online computation offloading in wireless powered mobile-edge computing networks[J].IEEE Transactions on Mobile Computing,2019,DOI:10.1109/TMC.2019.2928811.
[17] Mnih V,Badia A P,Mirza L,et al.Asynchronous methods for deep reinforcement learning[A].Proceedings of the 33rd International Conference on Machine Learning (ICML)[C].New York,USA:IMLS,2016.1928-1937.
[18] Zeinali Y,Story B A.Competitive probabilistic neural network[J].Integrated Computer-Aided Engineering,2017,24(2):105-118.
[19] Kaing D,Medsker L.Competitive hybrid ensemble using neural network and decision tree[J].Advances in Intelligent Systems and Computing,2018,648(28):147-155. |