With the rapid development of the Industrial Internet of Things(IIoT),the traditional centralized cloud processing model has encountered the challenges of high communication latency and high energy consumption in hand...With the rapid development of the Industrial Internet of Things(IIoT),the traditional centralized cloud processing model has encountered the challenges of high communication latency and high energy consumption in handling industrial big data tasks.This paper aims to propose a low-latency and lowenergy path computing scheme for the above problems.This scheme is based on the cloud-fog network architecture.The computing resources of fog network devices in the fog computing layer are used to complete task processing step by step during the data interaction from industrial field devices to the cloud center.A collaborative scheduling strategy based on the particle diversity discrete binary particle swarm optimization(PDBPSO)algorithm is proposed to deploy manufacturing tasks to the fog computing layer reasonably.The task in the form of a directed acyclic graph(DAG)is mapped to a factory fog network in the form of an undirected graph(UG)to find the appropriate computing path for the task,significantly reducing the task processing latency under energy consumption constraints.Simulation experiments show that this scheme’s latency performance outperforms the strategy that tasks are wholly offloaded to the cloud and the strategy that tasks are entirely offloaded to the edge equipment.展开更多
鉴于现阶段无线技术在工业控制系统应用中存在的问题,将UWB(U ltra W ideband)技术引入到工业控制网络中。提出了基于UWB的双频二级工业控制网络体系结构。同时,在此体系结构基础上设计了相应的通信模型和设备模型,并对此方案进行了分...鉴于现阶段无线技术在工业控制系统应用中存在的问题,将UWB(U ltra W ideband)技术引入到工业控制网络中。提出了基于UWB的双频二级工业控制网络体系结构。同时,在此体系结构基础上设计了相应的通信模型和设备模型,并对此方案进行了分析和评价。该方案在系统级上部分缓解了无线技术在工业环境中实时性和可靠性先天不足的问题。展开更多
基金supported by the Shaanxi Key R&D Program Project(2021GY-100).
文摘With the rapid development of the Industrial Internet of Things(IIoT),the traditional centralized cloud processing model has encountered the challenges of high communication latency and high energy consumption in handling industrial big data tasks.This paper aims to propose a low-latency and lowenergy path computing scheme for the above problems.This scheme is based on the cloud-fog network architecture.The computing resources of fog network devices in the fog computing layer are used to complete task processing step by step during the data interaction from industrial field devices to the cloud center.A collaborative scheduling strategy based on the particle diversity discrete binary particle swarm optimization(PDBPSO)algorithm is proposed to deploy manufacturing tasks to the fog computing layer reasonably.The task in the form of a directed acyclic graph(DAG)is mapped to a factory fog network in the form of an undirected graph(UG)to find the appropriate computing path for the task,significantly reducing the task processing latency under energy consumption constraints.Simulation experiments show that this scheme’s latency performance outperforms the strategy that tasks are wholly offloaded to the cloud and the strategy that tasks are entirely offloaded to the edge equipment.
文摘鉴于现阶段无线技术在工业控制系统应用中存在的问题,将UWB(U ltra W ideband)技术引入到工业控制网络中。提出了基于UWB的双频二级工业控制网络体系结构。同时,在此体系结构基础上设计了相应的通信模型和设备模型,并对此方案进行了分析和评价。该方案在系统级上部分缓解了无线技术在工业环境中实时性和可靠性先天不足的问题。
