Design of an Improved Method for Task Scheduling Using Proximal Policy Optimization and Graph Neural Networks
Modern computational environments have been getting more and more complex and dynamic; hence, mechanisms of task scheduling are increasingly sophisticated in order to guarantee optimal resource usage and reduced latency. Traditional heuristic-based approaches, although very fast, often fail to meet...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2024-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10755085/ |
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