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Cloud control for IIoT in a cloud-edge environment
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The industrial Internet of Things(IIoT)is a new indus-trial idea that combines the latest information and communica-tion technologies with the industrial economy.In this paper,a cloud control structure is designed for IIoT in cloud-edge envi-ronment with three modes of 5G.For 5G based IIoT,the time sensitive network(TSN)service is introduced in transmission network.A 5G logical TSN bridge is designed to transport TSN streams over 5G framework to achieve end-to-end configuration.For a transmission control protocol(TCP)model with nonlinear disturbance,time delay and uncertainties,a robust adaptive fuzzy sliding mode controller(AFSMC)is given with control rule parameters.IIoT workflows are made up of a series of subtasks that are linked by the dependencies between sensor datasets and task flows.IIoT workflow scheduling is a non-deterministic polynomial(NP)-hard problem in cloud-edge environment.An adaptive and non-local-convergent particle swarm optimization(ANCPSO)is designed with nonlinear inertia weight to avoid falling into local optimum,which can reduce the makespan and cost dramatically.Simulation and experiments demonstrate that ANCPSO has better performances than other classical algo-rithms.
5G and time sensitive network(TSN)industrial Internet of Things(IIoT)workflowtransmission control protocol(TCP)flows controlcloud edge collaborationmulti-objective optimal scheduling
YAN Ce、XIA Yuanqing、YANG Hongjiu、ZHAN Yufeng
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School of Automation,Beijing Institute of Technology,Beijing 100081,China
School of Electrical and Information Engineering,Tianjin University,Tianjin 300072,China
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