Deep Reinforcement Learning-Based Service-Oriented Resource Allocation in Smart Grids

Deep Reinforcement Learning-Based Service-Oriented Resource Allocation in Smart Grids

Resource allocation has a direct and profound impact on the performance of resource-limited smart grids with diversified services that need to be timely processed. In this paper, we investigate a joint communication, computing, and caching resource allocation problem with distinct delay requirement...

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Bibliographic Details
Main Authors: Linhan Xi, Ying Wang, Yang Wang, Zhihui Wang, Xue Wang, Yuanbin Chen
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Smart grids
edge computing
deep reinforcement learning
resource allocation
Online Access:https://ieeexplore.ieee.org/document/9437185/

Internet

https://ieeexplore.ieee.org/document/9437185/

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