为解决在IIoT(industrial internet of things)环境下,现有的调度算法调度工作流中通信频繁、数据传输量大的任务所带来的完工时间上升、成本增加等影响的问题,提出一种基于聚类的工作流多雾协同调度算法。通过二分K均值算法对工作流中...为解决在IIoT(industrial internet of things)环境下,现有的调度算法调度工作流中通信频繁、数据传输量大的任务所带来的完工时间上升、成本增加等影响的问题,提出一种基于聚类的工作流多雾协同调度算法。通过二分K均值算法对工作流中的任务进行聚类,基于聚类结果,在多个雾服务器之间使用改进的免疫粒子群优化算法进行任务调度。实验结果表明,该算法相比其它一些传统的调度算法在完工时间、成本、负载均衡方面都有一定提升。展开更多
为了解决在工业物联网(industrial Internet of things,IIoT)环境下,现有的调度算法在调度工作流中对数据安全、响应时间有一定要求的任务所带来的完工时间上升、成本增加的问题,提出一种基于雾环境负载率而变化的任务调度策略,并使用...为了解决在工业物联网(industrial Internet of things,IIoT)环境下,现有的调度算法在调度工作流中对数据安全、响应时间有一定要求的任务所带来的完工时间上升、成本增加的问题,提出一种基于雾环境负载率而变化的任务调度策略,并使用改进的蜣螂优化算法对工作流调度问题进行求解。改进的算法使用HEFT(heterogeneous earliest finish time)算法对蜣螂种群进行初始化,降低了原始算法中随机性带来的影响。同时引入了镜面反射和反向学习思想,提高了算法的搜索性能。实验结果表明,该算法相比于其他一些传统的调度算法在完工时间与成本方面都有一定的性能提升。展开更多
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...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.展开更多
工业物联网(Industrial Internet of Things,IIoT)是第六代移动通信系统(6th Generation Mobile Communication System,6G)的典型应用。提出了一种新的基于几何的工业物联网环境非平稳随机模型(Geometry-based Stochastic Model,GBSM)...工业物联网(Industrial Internet of Things,IIoT)是第六代移动通信系统(6th Generation Mobile Communication System,6G)的典型应用。提出了一种新的基于几何的工业物联网环境非平稳随机模型(Geometry-based Stochastic Model,GBSM)。该模型通过速度分解细化IIoT下信道模型中散射体组成的簇的生灭过程,对不同运动方向间信道非平稳特性的区别进行了建模。仿真结果表明,该模型能较好地表征不同运动方向对信道特性的影响,能够有效地反映信道传播环境中簇的数量。与参考模型以及射线追踪仿真的时延均方扩展和角度均方扩展拟合结果验证了该模型具有较高的精度。展开更多
With the rapid development of data applications in the scene of Industrial Internet of Things(IIoT),how to schedule resources in IIoT environment has become an urgent problem to be solved.Due to benefit of its strong ...With the rapid development of data applications in the scene of Industrial Internet of Things(IIoT),how to schedule resources in IIoT environment has become an urgent problem to be solved.Due to benefit of its strong scalability and compatibility,Kubernetes has been applied to resource scheduling in IIoT scenarios.However,the limited types of resources,the default scheduling scoring strategy,and the lack of delay control module limit its resource scheduling performance.To address these problems,this paper proposes a multi-resource scheduling(MRS)scheme of Kubernetes for IIoT.The MRS scheme dynamically balances resource utilization by taking both requirements of tasks and the current system state into consideration.Furthermore,the experiments demonstrate the effectiveness of the MRS scheme in terms of delay control and resource utilization.展开更多
工业设备接入网络实现生产自动化的过程中数据量级快速增长,而边缘层设备资源有限,无法完成全部任务请求。针对边缘层设备合理高效处理端设备任务请求的问题,提出了一种基于多跳计算卸载方法的物联网边缘网关(Internet of Things Edge G...工业设备接入网络实现生产自动化的过程中数据量级快速增长,而边缘层设备资源有限,无法完成全部任务请求。针对边缘层设备合理高效处理端设备任务请求的问题,提出了一种基于多跳计算卸载方法的物联网边缘网关(Internet of Things Edge Gateway,IoTEG)框架。该框架要求数据优先在网关侧处理以降低时延和保护隐私。首先,该框架根据端设备任务流特点将其分为时敏和非时敏两类。其次,设计了任务轮转调度处理机制,对任务流按时延要求高低进行处理。最后,设计了基于实时网络资源、实时本地资源和任务类型的最优联合计算卸载策略。实验结果表明,IoTEG框架能有效提高任务卸载的成功率,并能够高效处理不同类型的任务。展开更多
文摘为解决在IIoT(industrial internet of things)环境下,现有的调度算法调度工作流中通信频繁、数据传输量大的任务所带来的完工时间上升、成本增加等影响的问题,提出一种基于聚类的工作流多雾协同调度算法。通过二分K均值算法对工作流中的任务进行聚类,基于聚类结果,在多个雾服务器之间使用改进的免疫粒子群优化算法进行任务调度。实验结果表明,该算法相比其它一些传统的调度算法在完工时间、成本、负载均衡方面都有一定提升。
文摘为了解决在工业物联网(industrial Internet of things,IIoT)环境下,现有的调度算法在调度工作流中对数据安全、响应时间有一定要求的任务所带来的完工时间上升、成本增加的问题,提出一种基于雾环境负载率而变化的任务调度策略,并使用改进的蜣螂优化算法对工作流调度问题进行求解。改进的算法使用HEFT(heterogeneous earliest finish time)算法对蜣螂种群进行初始化,降低了原始算法中随机性带来的影响。同时引入了镜面反射和反向学习思想,提高了算法的搜索性能。实验结果表明,该算法相比于其他一些传统的调度算法在完工时间与成本方面都有一定的性能提升。
文摘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.
文摘工业物联网(Industrial Internet of Things,IIoT)是第六代移动通信系统(6th Generation Mobile Communication System,6G)的典型应用。提出了一种新的基于几何的工业物联网环境非平稳随机模型(Geometry-based Stochastic Model,GBSM)。该模型通过速度分解细化IIoT下信道模型中散射体组成的簇的生灭过程,对不同运动方向间信道非平稳特性的区别进行了建模。仿真结果表明,该模型能较好地表征不同运动方向对信道特性的影响,能够有效地反映信道传播环境中簇的数量。与参考模型以及射线追踪仿真的时延均方扩展和角度均方扩展拟合结果验证了该模型具有较高的精度。
基金This work was supported by the National Natural Science Foundation of China(61872423)the Industry Prospective Primary Research&Development Plan of Jiangsu Province(BE2017111)the Scientific Research Foundation of the Higher Education Institutions of Jiangsu Province(19KJA180006).
文摘With the rapid development of data applications in the scene of Industrial Internet of Things(IIoT),how to schedule resources in IIoT environment has become an urgent problem to be solved.Due to benefit of its strong scalability and compatibility,Kubernetes has been applied to resource scheduling in IIoT scenarios.However,the limited types of resources,the default scheduling scoring strategy,and the lack of delay control module limit its resource scheduling performance.To address these problems,this paper proposes a multi-resource scheduling(MRS)scheme of Kubernetes for IIoT.The MRS scheme dynamically balances resource utilization by taking both requirements of tasks and the current system state into consideration.Furthermore,the experiments demonstrate the effectiveness of the MRS scheme in terms of delay control and resource utilization.
文摘工业设备接入网络实现生产自动化的过程中数据量级快速增长,而边缘层设备资源有限,无法完成全部任务请求。针对边缘层设备合理高效处理端设备任务请求的问题,提出了一种基于多跳计算卸载方法的物联网边缘网关(Internet of Things Edge Gateway,IoTEG)框架。该框架要求数据优先在网关侧处理以降低时延和保护隐私。首先,该框架根据端设备任务流特点将其分为时敏和非时敏两类。其次,设计了任务轮转调度处理机制,对任务流按时延要求高低进行处理。最后,设计了基于实时网络资源、实时本地资源和任务类型的最优联合计算卸载策略。实验结果表明,IoTEG框架能有效提高任务卸载的成功率,并能够高效处理不同类型的任务。
