MRLCC: an adaptive cloud task scheduling method based on meta reinforcement learning
Abstract Task scheduling is a complex problem in cloud computing, and attracts many researchers’ interests. Recently, many deep reinforcement learning (DRL)-based methods have been proposed to learn the scheduling policy through interacting with the environment. However, most DRL methods focus on a...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2023-05-01
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| Series: | Journal of Cloud Computing: Advances, Systems and Applications |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s13677-023-00440-8 |