Deep Reinforcement Learning-Based Workload Scheduling for Edge Computing

Deep Reinforcement Learning-Based Workload Scheduling for Edge Computing

Abstract Edge computing is a new paradigm for providing cloud computing capacities at the edge of network near mobile users. It offers an effective solution to help mobile devices with computation-intensive and delay-sensitive tasks. However, the edge of network presents a dynamic environment with l...

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Bibliographic Details
Main Authors: Tao Zheng, Jian Wan, Jilin Zhang, Congfeng Jiang
Format: Article
Language:English
Published: SpringerOpen 2022-01-01
Series:Journal of Cloud Computing: Advances, Systems and Applications
Subjects:
Edge computing
Computation offloading
Workload scheduling
Deep reinforcement learning
Online Access:https://doi.org/10.1186/s13677-021-00276-0

Internet

https://doi.org/10.1186/s13677-021-00276-0

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