Computation offloading strategy based on deep reinforcement learning for connected and autonomous vehicle in vehicular edge computing
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Title
Computation offloading strategy based on deep reinforcement learning for connected and autonomous vehicle in vehicular edge computing
Authors
Keywords
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Journal
Journal of Cloud Computing-Advances Systems and Applications
Volume 10, Issue 1, Pages -
Publisher
Springer Science and Business Media LLC
Online
2021-06-08
DOI
10.1186/s13677-021-00246-6
References
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Related references
Note: Only part of the references are listed.- Multi-Armed Bandit Learning for Computation-Intensive Services in MEC-Empowered Vehicular Networks
- (2020) Penglin Dai et al. IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
- Deep Reinforcement Learning-Based Adaptive Computation Offloading for MEC in Heterogeneous Vehicular Networks
- (2020) Hongchang Ke et al. IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
- Vehicular Edge Computing and Networking: A Survey
- (2020) Lei Liu et al. MOBILE NETWORKS & APPLICATIONS
- Dependency-Aware Task Scheduling in Vehicular Edge Computing
- (2020) Yujiong Liu et al. IEEE Internet of Things Journal
- Deep-Reinforcement-Learning-Based Offloading Scheduling for Vehicular Edge Computing
- (2020) Wenhan Zhan et al. IEEE Internet of Things Journal
- EEDTO: An Energy-Efficient Dynamic Task Offloading Algorithm for Blockchain-Enabled IoT-Edge-Cloud Orchestrated Computing
- (2020) Huaming Wu et al. IEEE Internet of Things Journal
- Volunteer Assisted Collaborative Offloading and Resource Allocation in Vehicular Edge Computing
- (2020) Feng Zeng et al. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
- Adaptive Computation Offloading With Edge for 5G-Envisioned Internet of Connected Vehicles
- (2020) Xiaolong Xu et al. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
- Computation Offloading and Resource Allocation For Cloud Assisted Mobile Edge Computing in Vehicular Networks
- (2019) Junhui Zhao et al. IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
- Deep Reinforcement Learning for Vehicular Edge Computing
- (2019) Zhaolong Ning et al. ACM Transactions on Intelligent Systems and Technology
- Delay-Sensitive Task Offloading in the 802.11p-Based Vehicular Fog Computing Systems
- (2019) Qiong Wu et al. IEEE Internet of Things Journal
- Multi-Objective Decision-Making for Mobile Cloud Offloading: A Survey
- (2018) Huaming Wu IEEE Access
- Chimera: An Energy-efficient and Deadline-aware Hybrid Edge Computing Framework for Vehicular Crowdsensing Applications
- (2018) Lingjun Pu et al. IEEE Internet of Things Journal
- FiWi-Enhanced Vehicular Edge Computing Networks: Collaborative Task Offloading
- (2018) Hongzhi Guo et al. IEEE Vehicular Technology Magazine
- Traffic and Computation Co-Offloading With Reinforcement Learning in Fog Computing for Industrial Applications
- (2018) Yixuan Wang et al. IEEE Transactions on Industrial Informatics
- Joint Load Balancing and Offloading in Vehicular Edge Computing and Networks
- (2018) Yueyue Dai et al. IEEE Internet of Things Journal
- AVE: Autonomous Vehicular Edge Computing Framework with ACO-Based Scheduling
- (2017) Jingyun Feng et al. IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
- Mobile-Edge Computing for Vehicular Networks: A Promising Network Paradigm with Predictive Off-Loading
- (2017) Ke Zhang et al. IEEE Vehicular Technology Magazine
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