Reinforcement Learning for Joint Caching and Power Control for IIoT Networks
Minimizing the Age of Information (AoI) violation probability is essential for reliable and timely data delivery in MEC-enabled IIoT networks. This study proposes the Joint Caching and Power Control (JCPC) scheme, leveraging Deep Deterministic Policy Gradient (DDPG) to optimize caching decisions and power allocation under system-level AoI and power constraints. Simulations validate that JCPC outperforms baseline strategies, significantly reducing AoI violation probability and improving the efficiency of MEC-enabled IIoT networks.
Authors
- Tan Zheng Hui Ernest (ORCID: https://orcid.org/0000-0001-8978-8989)
- Ritabrata Maiti (ORCID: https://orcid.org/0000-0003-3022-3064)
- A S Madhukumar
Institutions
- Singapore Institute of Technology (SG)
- Nanyang Technological University (SG)
Publication Details
- Published
- 2025-06-17
- DOI
- https://doi.org/10.1109/vtc2025-spring65109.2025.11174365
- Primary Topic
- Caching and Content Delivery
- Type
- article
- Field-Weighted Citation Impact
- 0.00