journal article·2024Open access

A Task Offloading Strategy Based on Multi-Agent Deep Reinforcement Learning for Offshore Wind Farm Scenarios

Zeshuang Song, Xiao Wang, Qing Wu, Yanting Tao, Linghua Xu, Yaohua Yin, Jianguo Yan

Computers, Materials & Continua· Volume 81· Issue 1

Abstract

This research is the first application of Unmanned Aerial Vehicles (UAVs) equipped with Multi-access Edge Computing (MEC) servers to offshore wind farms, providing a new task offloading solution to address the challenge of sc... | Find, read and cite all the research you need on Tech Science Press
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Research context

OpenAlex topics: Energy Load and Power Forecasting · Reinforcement Learning in Robotics

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

References (41)

Show source-provided references
1. Planning of MTDC system for offshore wind farm clusters considering wind power curtailment caused by failure
2. Development of offshore wind power and foundation technology for offshore wind turbines in China10.1016/j.oceaneng.2022.113256 ↗
3. Dark green electricity comes from the sea: Capitalizing on ecological merits of offshore wind power?10.1016/j.rser.2014.10.043 ↗
4. Review of recent offshore wind turbine research and optimization methodologies in their design
5. Vibration performance, stability and energy transfer of wind turbine tower via PD controller
6. Remotely monitoring offshore wind turbines via ZigBee networks embedded with an advanced routing strategy10.1063/1.4773467 ↗
7. Flagg · Global Oceans 2020: Singapore–US Gulf Coast · 2020 · 3 · 1
8. A reinforcement learning based edge cloud collaboration
9. An edge-computing framework for operational modal analysis of offshore wind-turbine tower
10. Joint deployment and trajectory optimization in UAV-assisted vehicular edge computing networks10.23919/JCN.2021.000026 ↗
11. When deep reinforcement learning meets federated learning: Intelligent multitimescale resource management for multiaccess edge computing in 5G ultradense network10.1109/JIOT.2020.3026589 ↗
12. Cost optimization of UAV-MEC network calculation offloading: A multi-agent reinforcement learning method
13. Decentralized computation offloading for multi-user mobile edge computing: A deep reinforcement learning approach
14. An efficient computation offloading and resource allocation algorithm in RIS empowered MEC10.1016/j.comcom.2022.10.012 ↗
15. Optimization scheme of trusted task offloading in IIoT scenario based on DQN
16. Generative adversarial LSTM networks learning for resource allocation in UAV-Served M2M communications10.1109/LWC.2021.3075467 ↗
17. Incentive techniques for the internet of things: A survey
18. Fast adaptive task offloading and resource allocation via multiagent reinforcement learning in heterogeneous vehicular fog computing10.1109/JIOT.2022.3228246 ↗
19. Task partitioning and offloading in DNN-task enabled mobile edge computing networks10.1109/TMC.2021.3114193 ↗
20. Hierarchical multi-agent deep reinforcement learning for energy-efficient hybrid computation offloading10.1109/TVT.2022.3202525 ↗
21. Energy-aware and mobility-driven computation offloading in MEC10.1007/s10723-023-09654-1 ↗
22. Wireless edge device intelligent task offloading in mobile edge computing using hyper-heuristics10.1186/s13634-022-00965-1 ↗
23. Energy-efficient resource allocation for D2D-assisted fog computing10.1109/TGCN.2022.3190085 ↗
24. Auction design for edge computation offloading in sdn-based ultra dense networks10.1109/TMC.2020.3026319 ↗
25. Multi-agent DDPG enpowered uav trajectory optimization for computation task offloading
26. Deep reinforcement learning-based one-to-multiple cooperative computing in large-scale event-driven wireless sensor networks
27. HAMEC-RSMA: Enhanced aerial computing systems with rate splitting multiple access10.1109/ACCESS.2022.3173125 ↗
28. Deep reinforcement learning-based adaptive computation offloading for MEC in heterogeneous vehicular networks10.1109/TVT.2020.2993849 ↗
29. Unprecedented Smart algorithm for uninterrupted sdn services during DDoS attack
30. Multi-agent deep reinforcement learning-based partial task offloading and resource allocation in edge computing environment10.3390/electronics11152394 ↗
31. Joint sensing, communication, and computation resource allocation for cooperative perception in fog-based vehicular networks
32. A federated learning and deep reinforcement learning-based method with two types of agents for computation offload
33. Energy-efficient resource allocation for mobile-edge computation offloading10.1109/TWC.2016.2633522 ↗
34. JUTAR: Joint user-association, task-partition, and resource-allocation algorithm for MEC networks
35. Blockchain-enabled task offloading with energy harvesting in multi-uav-assisted IoT networks: A multi-agent drl approach10.1109/JSAC.2022.3213352 ↗
36. Deep reinforcement learning based computation offloading and trajectory planning for multi-uav cooperative target search10.1109/JSAC.2022.3228558 ↗
37. Deadline-aware task offloading with partially-observable deep reinforcement learning for multi-access edge computing10.1109/TNSE.2021.3115054 ↗
38. Intelligent delay-aware partial computing task offloading for multiuser industrial internet of things through edge computing10.1109/JIOT.2021.3123406 ↗
39. Research on hybrid computation offloading strategy for MEC based on DDPG10.3390/electronics12030562 ↗
40. Task scheduling based on adaptive priority experience replay on cloud platforms
41. Learning-based joint optimization of energy delay and privacy in multiple-user edge-cloud collaboration MEC systems10.1109/JIOT.2021.3088607 ↗