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[HTML][HTML] Deep reinforcement learning-based scheduling for optimizing system load and response time in edge and fog computing environments

Z Wang, M Goudarzi, M Gong, R Buyya - Future Generation Computer …, 2024 - Elsevier
Edge/fog computing, as a distributed computing paradigm, satisfies the low-latency
requirements of ever-increasing number of IoT applications and has become the …
被引用次数：18 相关文章

Deep Reinforcement Learning-based scheduling for optimizing system load and response time in edge and fog computing environments

Z Wang, M Goudarzi, M Gong, R Buyya - 2024 - dl.acm.org
Edge/fog computing, as a distributed computing paradigm, satisfies the low-latency
requirements of ever-increasing number of IoT applications and has become the …

Deep Reinforcement Learning-based Scheduling for Optimizing System Load and Response Time in Edge and Fog Computing Environments

Z Wang, M Goudarzi, M Gong, R Buyya - arXiv e-prints, 2023 - ui.adsabs.harvard.edu
Edge/fog computing, as a distributed computing paradigm, satisfies the low-latency
requirements of ever-increasing number of IoT applications and has become the …