NIST · ИТ · 5aa95271f3d71423ebc5
Deep Reinforcement Learning for Edge Service Placement in Softwarized Industrial Cyber-Physical System
Future industrial cyber-physical system (CPS) devices are expected to request a large amount of delay-sensitive services that need to be processed at the edge of a network. Due to limited resources, service placement at the edge of the cloud has attracted
NIST · ИТОфициальный источник · 2021-05-06
{
"title_en": "Deep Reinforcement Learning for Edge Service Placement in Softwarized Industrial Cyber-Physical System",
"designation": "",
"series": "",
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"date": "2021-05-06",
"date_original": "May 6, 2021",
"url": "https://www.nist.gov/publications/deep-reinforcement-learning-edge-service-placement-softwarized-industrial-cyber",
"source": "NIST Publications",
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"authors_en": "Hamid Gharavi",
"abstract_excerpt_en": "Future industrial cyber-physical system (CPS) devices are expected to request a large amount of delay-sensitive services that need to be processed at the edge of a network. Due to limited resources, service placement at the edge of the cloud has attracted",
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{
"title_en": "Deep Reinforcement Learning for Edge Service Placement in Softwarized Industrial Cyber-Physical System",
"designation": "",
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"date": "2021-05-06",
"date_original": "May 6, 2021",
"url": "https://www.nist.gov/publications/deep-reinforcement-learning-edge-service-placement-softwarized-industrial-cyber",
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"authors_en": "Hamid Gharavi",
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