Fetching the paper…
Reading the bibliography…
The smart vehicles construct Vehicle of Internet which can execute various intelligent services.
B. Mao, Z. M. Fadlullah, F. Tang, N. Kato, et al., “Routing or Computing? The Paradigm Shift Towards Intelligent Computer Network Packet Transmission Based on Deep Learning,” IEEE Trans. on Computer , 66 (11), 2017, pp. 1946-1960
1960
Earlier work this paper cites.
Y. B. Lin, “Reducing location update cost in a PCS network,” IEEE Transactions on Networking , vol. 5, no. 1, pp. 25-33, 1997
1997
Earlier work this paper cites.
V. Mnih, K. Kavukcuoglu, D. Silver, “Human-level control through deep reinforcement learning,” Nature , vol. 518, pp. 529-534, Feb. 2015
2015
Earlier work this paper cites.
X. Hou, Y. Li, M. Chen, D. Wu, D. Jin, S. Chen, “Vehicular Fog Computing: A viewpoint of Vehicles as the Infrastructure,” IEEE Trans. Vehicular Tech. , vol. 65, no. 6, pp. 3860 - 3873, Jun. 2016
2016
Earlier work this paper cites.
R. Kim, H. Lim, B. Krishnamachari, “Prefetching-Based Data Dissemination in Vehicular Cloud Systems,” IEEE Trans. Vehicular Tech. , vol. 65, no. 1, pp. 292-306, Jan. 2016
2016
Earlier work this paper cites.
C. Wang ; Y. Li ; D. Jin ; S. Chen, “On the Serviceability of Mobile Vehicular Cloudlets in a Large-Scale Urban Environment”, IEEE Trans. Intelligent Transportation Systems. , vol.17, no. 10, pp. 2960 - 2970, Oct. 2016
2016
Earlier work this paper cites.
X. Chen, L. Jiao, W. Li, X. Fu, “Efficient Multi-User Computation Offloading for Mobile-Edge Cloud Computing,” IEEE/ACM Trans. Netw. , vol. 24, no. 5, pp. 2795 - 2808, Oct. 2016
2016
Earlier work this paper cites.
Y. Mao, J. Zhang, K. B. Letaief, “Dynamic Computation Offloading for Mobile-Edge Computing with Energy Harvesting Devices IEEE J. Sel. Areas in Commun. , vol. 34, no. 12, pp. 3590-3605, Dec. 2016
2016
Earlier work this paper cites.
X. Chen, L. Jiao, W. Li, X. Fu, “Efficient Multi-User Computation Offloading for Mobile-Edge Cloud Computing IEEE/ACM Trans. Netw. , vol. 24, no. 5, pp. 2795-2808, Oct. 2016
2016
Earlier work this paper cites.
Y. Wang, M. Sheng, X. Wang, L. Wang, J. Li, “Mobile-Edge Computing: Partial Computation Offloading Using Dynamic Voltage Scaling,” IEEE Trans. on Commun. , vol. 64, no. 10, pp. 4268-4282, Oct. 2016
2016
Earlier work this paper cites.
V. Mnih, A. P. Badia, M. Mirza, et al. âAsynchronous methods for deep reinforcement learning,â? International Conference on Machine Learning (ICML) , Jun. 19-24 2016
2016
Cited alongside, same era.
H. Mao, M. Alizadeh, I. Menache et al., “Resource Management with Deep Reinforcement Learning,â? ACM Workshop on Hot Topics in Networks (HotNets) , Atlanta, USA, Nov. 09-10, 2016
2016
Cited alongside, same era.
K. Abboud, W. Zhuang, “Stochastic Analysis of Single-Hop Communication Link in Vehicular Ad Hoc Networks,” IEEE Trans. Vehicular Tech. , vol. 65, no. 1, pp. 226-240, 2016
2016
Cited alongside, same era.
J. Redmon, S. Divvala, R. Girshick, A. Farhadi, “You only look once: Unified, real-time object detection, in proc IEEE Conference on Computer Vision and Pattern Recognition (CVPR) ,” June 2016, pp. 779-788
2016
Cited alongside, same era.
N. Liu, Z. Li, Z. Xu, J. Xu, S. Lin, Q. Qiu, J. Tang, Y. Wang, “A Hierarchical Framework of Cloud Resource Allocation and Power Management Using Deep Reinforcement Learning”, IEEE International Conference on Distributed Computing Systems (ICDCS) , Jun. 5-8 2017, pp. 372 - 382
2017
Later among the works it cites.
H. Mao, R. Netravali, M. Alizadeh, “Neural Adaptive Video Streaming with Pensieve,” ACM SIGCOMM , Aug. 21-25, 2017, pp.197-210
2017
Later among the works it cites.
H. Chen, J. Wang, Q. Qi, H. Sun, Y. Li, “Bilinear CNN Models for Food Recognition,” International Conference on Digital Image Computing: Techniques and Applications , 29 Nov.-1 Dec. 2017, pp. 1-6
2017
Later among the works it cites.
Y. Zheng, Y. Wang, L. Zhang, J. Wang, Q. Qi, “A Tag-Based Integrated Diffusion Model for Personalized Location Recommendation,” International Conference on Neural Information Processing , 14-17 Nov. 2017, pp. 324-334
2017
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
K. Zhang, Y. Mao, S. Leng, Y. He, Y. Zhang, “Mobile-Edge Computing for Vehicular Networks: A Promising Network Paradigm with Predictive Off-Loading,” IEEE Vehicular Technology Magazine , vol. 12, no. 2. pp. 36-44, Apr. 2017
2017
Cited alongside, same era.
X. Lyu, W. Ni, H. Tian, et al, “Optimal Schedule of Mobile Edge Computing for Internet of Things Using Partial Information IEEE J. Sel. Areas in Commun. , vol. 25, no. 11, pp. 2606-261, Nov. 2017
2017
Cited alongside, same era.
Y. Zhou, F. R. Yu, J. Chen, Y.. Kuo, “Resource Allocation for Information-Centric Virtualized Heterogeneous Networks with In-Network Caching and Mobile Edge Computing,” IEEE Trans. on Vehicular Tech. , vol. 66, no. 12, Dec. 2017, pp. 11339-11351
2017
Cited alongside, same era.
N. Kato, Zubair Md. Fadlullah,et al., “The Deep Learning Vision for the Heterogeneous Network Traffic Control Proposal, Challenges, and Future perspective IEEE Wirel. Commun. , vol. 24, no. 3, pp. 146-153, Jun. 2017
2017
Cited alongside, same era.
L. Lei, L. You, G. Dai, T. Xuan Vu, D. Yuan, S. Chatzinotas, “A Deep Learning Approach for Optimizing Content Delivering in Cache-Enabled HetNet,” International Symposium on Wireless Communication Systems (ISWCS) , Aug. 28-31, 2017, pp. 449-453
2017
Cited alongside, same era.
Y. He, Z. Zhang, F. R. Yu, et al., “Deep-Reinforcement-Learning-Based Optimization for Cache-Enabled Opportunistic Interference Alignment Wireless Networksâ? IEEE Trans. on Vehicular Technology , vol. 66, no. 11, pp. 10433-10444, Nov. 2017
2017
Cited alongside, same era.
X. Chen, L. Jiao, W. Li, X. Fu, “Efficient multi-user computation offloading for mobile-edge cloud computing,” IEEE Trans. Netw. , vol. 24, no. 5, pp. 2795-2808
Cited in the paper.
T. Liu, F. Chen, Y. Ma, Y. Xie, “An energy-efficient task scheduling for mobile devices based on cloud assistant,” Future Generation Computer Systems , vol.61, pp. 1-12
Cited in the paper.
Z. Xu, J. Tang, J. Meng, W. Zhang, Y. Wang, C. H. Liu, D. Yang, “Experience-driven Networking: A Deep Reinforcement Learning based Approach”, IEEE International Conference on Computer Communications (INFOCOM) , 15-19 April 2018
2018
Closest in time.
Y. Kim, J. Kwak, S. Chong,“Dual-side Optimization for Cost-Delay Tradeoff in Mobile Edge Computing, IEEE Trans. Vehicular Tech. , vol. 67, no. 2, pp. 1765-1781, Feb. 2018
2018
Closest in time.
H. Cao, J. Cai, “Distributed Multiuser Computation Offloading for Cloudlet-Based Mobile Cloud Computing: A Game-Theoretic Machine Learning Approach,” IEEE Trans. Vehicular Tech. , vol. 67, no. 1, pp. 752 - 764, Jan. 2018
2018
Closest in time.
N. C. Luong, Z. Xiong, P. Wang, D. Niyato, “Optimal auction for edge computing resource management in mobile blockchain networks: A deep learning approach,” IEEE International Conference on Communications (ICC) , May 20-24 2018
2018
Closest in time.
Y. Wei, F. Richard Yu, M. Song, Z. Han, “User Scheduling and Resource Allocation in HetNets with Hybrid Energy Supply: An Actor-Critic Reinforcement Learning Approach,” IEEE Trans. Wirel. Commun. , vol.17, no.1, Jan. 2018, pp. 680-692
2018
Closest in time.