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
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
从Internet发展历史及应用环境变化的角度讨论IoT(Internet of Things)提出背景、内涵、组成结构和体系结构等关键问题。在分析对IoT的典型定义的基础上,笔者认为"ITU把IoT作为Internet平台在应用领域实现人、机、和智能化物理对象...从Internet发展历史及应用环境变化的角度讨论IoT(Internet of Things)提出背景、内涵、组成结构和体系结构等关键问题。在分析对IoT的典型定义的基础上,笔者认为"ITU把IoT作为Internet平台在应用领域实现人、机、和智能化物理对象(SPO)信息全方位互通和实践普适计算理念的下一代Internet及其应用系统的概括"是对IoT更为合理的广义定义。以该定义为基础,全面地分析了"由多个用户域网(CPN)通过骨干通信子网互联"的基本组成结构,讨论了两类SPO-CPN的基本组成结构及其支撑技术;指出SPO的引入主要影响CPN资源网络中的接入部分,属于应用系统的范畴,对Internet基本技术影响甚微。笔者不赞同以欧盟为代表的把IoT定义为联物专用网的狭义定义,指出其IoT模型和体系结构研究混淆了网络平台与应用系统,实质上是网络应用系统模型和体系结构。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
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
One of the major challenges arising in internet of military things(IoMT)is accommodating massive connectivity while providing guaranteed quality of service(QoS)in terms of ultra-high reliability.In this regard,this pa...One of the major challenges arising in internet of military things(IoMT)is accommodating massive connectivity while providing guaranteed quality of service(QoS)in terms of ultra-high reliability.In this regard,this paper presents a class of code-domain nonorthogonal multiple accesses(NOMAs)for uplink ultra reliable networking of massive IoMT based on tactical datalink such as Link-16 and joint tactical information distribution system(JTIDS).In the considered scenario,a satellite equipped with Nr antennas servers K devices including vehicles,drones,ships,sensors,handset radios,etc.Nonorthogonal coded modulation,a special form of multiple input multiple output(MIMO)-NOMA is proposed.The discussion starts with evaluating the output signal to interference-plus-noise(SINR)of receiver filter,leading to the unveiling of a closed-form expression for overloading systems as the number of users is significantly larger than the number of devices admitted such that massive connectivity is rendered.The expression allows for the development of simple yet successful interference suppression based on power allocation and phase shaping techniques that maximizes the sum rate since it is equivalent to fixed-point programming as can be proved.The proposed design is exemplified by nonlinear modulation schemes such as minimum shift keying(MSK)and Gaussian MSK(GMSK),two pivotal modulation formats in IoMT standards such as Link-16 and JITDS.Numerical results show that near capacity performance is offered.Fortunately,the performance is obtained using simple forward error corrections(FECs)of higher coding rate than existing schemes do,while the transmit power is reduced by 6 dB.The proposed design finds wide applications not only in IoMT but also in deep space communications,where ultra reliability and massive connectivity is a keen concern.展开更多
针对工业物联网中业务需求多样性和服务质量(Quality of Service,QoS)要求差异性导致的网络资源利用低问题,提出一种基于深度强化学习的网络切片资源分配策略。该策略运用深度强化学习优化网络切片资源分配的准入控制,通过智能体在特定...针对工业物联网中业务需求多样性和服务质量(Quality of Service,QoS)要求差异性导致的网络资源利用低问题,提出一种基于深度强化学习的网络切片资源分配策略。该策略运用深度强化学习优化网络切片资源分配的准入控制,通过智能体在特定时间窗口内处理资源请求,并根据不同网络切片的QoS要求及请求准入结果进行资源的动态分配。实验结果表明,所提策略相比基准算法在提高网络收益、资源利用率和接收率方面分别提升了8.33%、9.84%和8.57%。该策略能够在保证服务质量的同时提高整个网络的效率和性能。展开更多
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。
文摘从Internet发展历史及应用环境变化的角度讨论IoT(Internet of Things)提出背景、内涵、组成结构和体系结构等关键问题。在分析对IoT的典型定义的基础上,笔者认为"ITU把IoT作为Internet平台在应用领域实现人、机、和智能化物理对象(SPO)信息全方位互通和实践普适计算理念的下一代Internet及其应用系统的概括"是对IoT更为合理的广义定义。以该定义为基础,全面地分析了"由多个用户域网(CPN)通过骨干通信子网互联"的基本组成结构,讨论了两类SPO-CPN的基本组成结构及其支撑技术;指出SPO的引入主要影响CPN资源网络中的接入部分,属于应用系统的范畴,对Internet基本技术影响甚微。笔者不赞同以欧盟为代表的把IoT定义为联物专用网的狭义定义,指出其IoT模型和体系结构研究混淆了网络平台与应用系统,实质上是网络应用系统模型和体系结构。
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.
基金supported in part by the National Natural Science Foundation of China(Grant Nos.61601346 and 62377039)the Natural Science Basic Research Plan in Shaanxi Province of China(Grant No.2018JQ6044)+2 种基金the Ministry of Industry and Information Technology of the People's Republic of China(Grant No.2023-276-1-1)the Fundamental Research Funds for the Central Universities,Northwestern Polytechnical University(Grant No.31020180QD089)the Aeronautical Science Foundation of China(Grant Nos.20200043053004 and 20200043053005)。
文摘One of the major challenges arising in internet of military things(IoMT)is accommodating massive connectivity while providing guaranteed quality of service(QoS)in terms of ultra-high reliability.In this regard,this paper presents a class of code-domain nonorthogonal multiple accesses(NOMAs)for uplink ultra reliable networking of massive IoMT based on tactical datalink such as Link-16 and joint tactical information distribution system(JTIDS).In the considered scenario,a satellite equipped with Nr antennas servers K devices including vehicles,drones,ships,sensors,handset radios,etc.Nonorthogonal coded modulation,a special form of multiple input multiple output(MIMO)-NOMA is proposed.The discussion starts with evaluating the output signal to interference-plus-noise(SINR)of receiver filter,leading to the unveiling of a closed-form expression for overloading systems as the number of users is significantly larger than the number of devices admitted such that massive connectivity is rendered.The expression allows for the development of simple yet successful interference suppression based on power allocation and phase shaping techniques that maximizes the sum rate since it is equivalent to fixed-point programming as can be proved.The proposed design is exemplified by nonlinear modulation schemes such as minimum shift keying(MSK)and Gaussian MSK(GMSK),two pivotal modulation formats in IoMT standards such as Link-16 and JITDS.Numerical results show that near capacity performance is offered.Fortunately,the performance is obtained using simple forward error corrections(FECs)of higher coding rate than existing schemes do,while the transmit power is reduced by 6 dB.The proposed design finds wide applications not only in IoMT but also in deep space communications,where ultra reliability and massive connectivity is a keen concern.
文摘针对工业物联网中业务需求多样性和服务质量(Quality of Service,QoS)要求差异性导致的网络资源利用低问题,提出一种基于深度强化学习的网络切片资源分配策略。该策略运用深度强化学习优化网络切片资源分配的准入控制,通过智能体在特定时间窗口内处理资源请求,并根据不同网络切片的QoS要求及请求准入结果进行资源的动态分配。实验结果表明,所提策略相比基准算法在提高网络收益、资源利用率和接收率方面分别提升了8.33%、9.84%和8.57%。该策略能够在保证服务质量的同时提高整个网络的效率和性能。
