Deep reinforcement learning based trajectory design and resource allocation for task-aware multi-UAV enabled MEC networks
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Title
Deep reinforcement learning based trajectory design and resource allocation for task-aware multi-UAV enabled MEC networks
Authors
Keywords
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Journal
COMPUTER COMMUNICATIONS
Volume -, Issue -, Pages -
Publisher
Elsevier BV
Online
2023-11-07
DOI
10.1016/j.comcom.2023.11.006
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- (2022) Andrey V. Savkin et al. IEEE Internet of Things Journal
- Multihop Task Routing in UAV-Assisted Mobile-Edge Computing IoT Networks With Intelligent Reflective Surfaces
- (2022) Yousef N. Shnaiwer et al. IEEE Internet of Things Journal
- Optimizing the Operation Cost for UAV-Aided Mobile Edge Computing
- (2021) Liang Zhang et al. IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
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- (2020) Zhe Yu et al. IEEE Internet of Things Journal
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- Energy-Efficient Resource Allocation and Trajectory Design for UAV Relaying Systems
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- UAV-Assisted Wireless Powered Cooperative Mobile Edge Computing: Joint Offloading, CPU Control, and Trajectory Optimization
- (2019) Yuan Liu et al. IEEE Internet of Things Journal
- Joint Altitude and Beamwidth Optimization for UAV-Enabled Multiuser Communications
- (2018) Haiyun He et al. IEEE COMMUNICATIONS LETTERS
- An Efficient Computation Offloading Management Scheme in the Densely Deployed Small Cell Networks With Mobile Edge Computing
- (2018) Fengxian Guo et al. IEEE-ACM TRANSACTIONS ON NETWORKING
- A Survey on Mobile Edge Computing: The Communication Perspective
- (2017) Yuyi Mao et al. IEEE Communications Surveys and Tutorials
- Joint Energy Minimization and Resource Allocation in C-RAN with Mobile Cloud
- (2016) Kezhi Wang et al. IEEE Transactions on Cloud Computing
- Human-level control through deep reinforcement learning
- (2015) Volodymyr Mnih et al. NATURE
- A Comprehensive Survey of Multiagent Reinforcement Learning
- (2008) L. Busoniu et al. IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART C-APPLICATIONS AND RE
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