Task Scheduling in Edge Network System Using Resource Interleaving and Reinforcement Learning
We propose a task scheduling method using resource interleaving and Reinforcement Learning (RL) for edge network system. We use resource interleaving to schedule edge node task forwarding to reduce task waiting delay on resources after being forwarded. We formulate a task scheduling optimization problem and use RL to ensure real-time policy. Simulations verify the proposed method’s effectiveness in task scheduling.
Authors
- Xinglong Pei (ORCID: https://orcid.org/0000-0001-9444-868X)
- Yongji Dong (ORCID: https://orcid.org/0009-0007-4480-6902)
- Dan Li (ORCID: https://orcid.org/0000-0003-2602-5532)
- Yuxiang Hu (ORCID: https://orcid.org/0009-0005-8536-3840)
Institutions
- Ministry of Education of the People's Republic of China (CN)
- PLA Information Engineering University (CN)
Publication Details
- Journal
- IEICE Transactions on Information and Systems
- Published
- 2025-03-09
- DOI
- https://doi.org/10.1587/transinf.2024edl8095
- Primary Topic
- IoT and Edge/Fog Computing
- Type
- article
- Field-Weighted Citation Impact
- 0.00