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- research-articleMarch 2024
Deep Reinforcement Learning-based scheduling for optimizing system load and response time in edge and fog computing environments
Future Generation Computer Systems (FGCS), Volume 152, Issue CPages 55–69https://doi.org/10.1016/j.future.2023.10.012AbstractEdge/fog computing, as a distributed computing paradigm, satisfies the low-latency requirements of ever-increasing number of IoT applications and has become the mainstream computing paradigm behind IoT applications. However, because large number ...
Highlights- A cost model for DAG-based applications to optimize load balancing and response time.
- A DRL-based technique to adaptively solve the weighted cost optimization problem.
- A practical scheduler in the FogBus2 serverless framework to ...