Deep Reinforcement Learning for Edge Service Placement in Softwarized Industrial Cyber-Physical System

Volume: 17, Issue: 8, Pages: 5552 - 5561
Published: Aug 1, 2021
Abstract
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 significant attention. Although there are many methods of design schemes, the service placement problem in industrial CPS has not been well studied. Furthermore, none of existing schemes can...
Paper Details
Title
Deep Reinforcement Learning for Edge Service Placement in Softwarized Industrial Cyber-Physical System
Published Date
Aug 1, 2021
Volume
17
Issue
8
Pages
5552 - 5561
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