| Residential College | false |
| Patent Number | PCT230622GZ |
| Status | 申請中 Pending |
| 基於深度强化學習的邊緣計算網絡中的任務時間優化方法 | |
| Year Issued | 2023-06-05 |
| 2023-06-05 | |
| Application Number | PCT230622GZ |
| Application Date | 2023-06-05 |
| Wu Yuan; Tan Pengcheng | |
| Country | China |
| Subtype | 发明专利 Invention |
| Abstract | This patent invents a task-processing latency optimization in edge computing networks. The invented methodology is based on the deep reinforcement learning and can effectively reduce the task-processing latency by flexibly scheduling different computation-tasks to different edge-nodes with heterogeneous computation-capacities. |
| Document Type | Patent |
| Collection | University of Macau |
| Affiliation | State Key Laboratory of Internet of Things for Smart City and the Department of Computer Information Science, University of Macau, Macau, China |
| First Author Affilication | University of Macau |
| Recommended Citation GB/T 7714 | Wu Yuan,Tan Pengcheng. 基於深度强化學習的邊緣計算網絡中的任務時間優化方法. PCT230622GZ[P]. 2023-06-05. |
| APA | Wu Yuan., & Tan Pengcheng (2023-06-05). 基於深度强化學習的邊緣計算網絡中的任務時間優化方法. |
| Files in This Item: | There are no files associated with this item. | |||||
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