One of the challenging scheduling problems in Cloud data centers is to take the allocation and migration of reconfigurable virtual machines as well as the integrated features of hosting physical machines into consider...One of the challenging scheduling problems in Cloud data centers is to take the allocation and migration of reconfigurable virtual machines as well as the integrated features of hosting physical machines into consideration. We introduce a Dynamic and Integrated Resource Scheduling algorithm (DAIRS) for Cloud data centers. Unlike traditional load-balance scheduling algorithms which often consider only one factor such as the CPU load in physical servers, DAIRS treats CPU, memory and network bandwidth integrated for both physical machines and virtual machines. We develop integrated measurement for the total imbalance level of a Cloud datacenter as well as the average imbalance level of each server. Simulation results show that DAIRS has good performance with regard to total imbalance level, average imbalance level of each server, as well as overall running time.展开更多
The rapid growth of low-Earth-orbit satellites has injected new vitality into future service provisioning.However,given the inherent volatility of network traffic,ensuring differentiated quality of service in highly d...The rapid growth of low-Earth-orbit satellites has injected new vitality into future service provisioning.However,given the inherent volatility of network traffic,ensuring differentiated quality of service in highly dynamic networks remains a significant challenge.In this paper,we propose an online learning-based resource scheduling scheme for satellite-terrestrial integrated networks(STINs)aimed at providing on-demand services with minimal resource utilization.Specifically,we focus on:①accurately characterizing the STIN channel,②predicting resource demand with uncertainty guarantees,and③implementing mixed timescale resource scheduling.For the STIN channel,we adopt the 3rd Generation Partnership Project channel and antenna models for non-terrestrial networks.We employ a one-dimensional convolution and attention-assisted long short-term memory architecture for average demand prediction,while introducing conformal prediction to mitigate uncertainties arising from burst traffic.Additionally,we develop a dual-timescale optimization framework that includes resource reservation on a larger timescale and resource adjustment on a smaller timescale.We also designed an online resource scheduling algorithm based on online convex optimization to guarantee long-term performance with limited knowledge of time-varying network information.Based on the Network Simulator 3 implementation of the STIN channel under our high-fidelity satellite Internet simulation platform,numerical results using a real-world dataset demonstrate the accuracy and efficiency of the prediction algorithms and online resource scheduling scheme.展开更多
In view of the fact that traditional job shop scheduling only considers a single factor, which affects the effect of resource allocation, the dual-resource integrated scheduling problem between AGV and machine in inte...In view of the fact that traditional job shop scheduling only considers a single factor, which affects the effect of resource allocation, the dual-resource integrated scheduling problem between AGV and machine in intelligent manufacturing job shop environment was studied. The dual-resource integrated scheduling model of AGV and machine was established by comprehensively considering constraints of machines, workpieces and AGVs. The bidirectional single path fixed guidance system based on topological map was determined, and the AGV transportation task model was defined. The improved A* path optimization algorithm was used to determine the optimal path, and the path conflict elimination mechanism was described. The improved NSGA-Ⅱ algorithm was used to determine the machining workpiece sequence, and the competition mechanism was introduced to allocate AGV transportation tasks. The proposed model and method were verified by a workshop production example, the results showed that the dual resource integrated scheduling strategy of AGV and machine is effective.展开更多
Nowadays,emergency accidents could happen at any time.The accidents occur unpredictably and the accidents requirements are diversely.The accidents happen in a dynamic environment and the resource should be cooperative...Nowadays,emergency accidents could happen at any time.The accidents occur unpredictably and the accidents requirements are diversely.The accidents happen in a dynamic environment and the resource should be cooperative to solve the accidents.Most methods are focusing on minimizing the casualties and property losses in a static environment.However,they are lack in considering the dynamic and unpredictable event handling.In this paper,we propose a representative environmental model in representation of emergency and dynamic resource allocation model,and an adaptive mathematical model based on Genetic Algorithm(GA)to generate an optimal set of solution domain.The experimental results show that the proposed algorithm can get a set of better candidate solutions.展开更多
Recently the integrated modular avionics （IMA） architecture which introduces the concept of resource partitioning becomes popular as an alternative to the traditional federated architecture. A novel hierarchical app...Recently the integrated modular avionics （IMA） architecture which introduces the concept of resource partitioning becomes popular as an alternative to the traditional federated architecture. A novel hierarchical approach is proposed to solve the resource allocation problem for IMA systems in distributed environments. Firstly, the worst case response time of tasks with arbitrary deadlines is analyzed for the two-level scheduler. Then, the hierarchical resource allocation approach is presented in two levels. At the platform level, a task assignment algorithm based on genetic simulated annealing （GSA） is proposed to assign a set of pre-defined tasks to different processing nodes in the form of task groups, so that resources can be allocated as partitions and mapped to task groups. While yielding to all the resource con- straints, the algorithm tries to find an optimal task assignment with minimized communication costs and balanced work load. At the node level, partition parameters are optimized, so that the computational resource can be allocated further. An example is shown to illustrate the hierarchal resource allocation approach and manifest the validity. Simulation results comparing the performance of the proposed GSA with that of traditional genetic algorithms are presented in the context of task assignment in IMA systems.展开更多
The practical engineering of satellite tracking telemetry and command(TT&C)is often disturbed by unpredictable external factors,including the temporary rise in a significant quantity of satellite TT&C tasks,te...The practical engineering of satellite tracking telemetry and command(TT&C)is often disturbed by unpredictable external factors,including the temporary rise in a significant quantity of satellite TT&C tasks,temporary failures and failures of some TT&C resources,and so on.To improve the adaptability and robustness of satellite TT&C systems when faced with uncertain dynamic disturbances,a hierarchical disturbance propagation mechanism and an improved contract network dynamic scheduling method for satellite TT&C resources were designed to address the dynamic scheduling problem of satellite TT&C resources.Firstly,the characteristics of the dynamic scheduling problem of satellite TT&C resources are analyzed,and a mathematical model is established with the weighted optimization objectives of maximizing the revenue from task completion and minimizing the degree of plan disturbance.Then,a bottom-up distributed dynamic collaborative scheduling framework for satellite TT&C resources is proposed,which includes a task layer,a resource layer,a central internal collaboration layer,and a central external collaboration layer.Dynamic disturbances are propagated layer by layer from the task layer to the central external collaboration layer in a bottom-up manner,using efficient heuristic strategies in the task layer and the resource layer,respectively.We use improved contract network algorithms in the center internal collaboration layer and the center external collaboration layer,the original scheduling plan is quickly adjusted to minimize the impact of disturbances while effectively completing dynamic task requirements.Finally,a large number of simulation experiments were carried out and compared with various comparative algorithms.The results show that the proposed algorithm can effectively improve the solution effect of satellite TT&C resource dynamic scheduling problems,and has good application prospects.展开更多
近年来,网络功能虚拟化(NFV)以其网络设备功能解耦和无缝交互等优势,逐步成为现代网络设计的核心技术。其中,SD-WAN(Software Defined Wide Area Network)以其可编程性和灵活性,为NFV应用的场景提供了广阔的空间。文中以SD-WAN实际应用...近年来,网络功能虚拟化(NFV)以其网络设备功能解耦和无缝交互等优势,逐步成为现代网络设计的核心技术。其中,SD-WAN(Software Defined Wide Area Network)以其可编程性和灵活性,为NFV应用的场景提供了广阔的空间。文中以SD-WAN实际应用为背景,探讨了NFV在其中的作用和优化策略。首先,建立了一个SD-WAN环境,采用网络功能虚拟化技术,实现了如防火墙,负载均衡等核心网络功能的动态配置和部署。实验结果表明,相对于传统的物理设备,NFV技术在不影响网络性能的同时,降低了设备成本和维护成本。然后,针对SD-WAN的特点,提出了一种资源调度优化算法,其能根据实时网络状况,动态调整虚拟网络功能的资源分配,从而进一步提高其性能。通过实验证明,该优化策略可有效提升整体网络的灵活性、稳定性和效能,这为SD-WAN的实际应用场景提供了有效的优化策略参考,有助于推动NFV在SD-WAN等宽域网络中的进一步应用。展开更多
基金supported by Scientific Research Foundation for the Returned Overseas Chinese ScholarsState Education Ministry under Grant No.2010-2011 and Chinese Post-doctoral Research Foundation
文摘One of the challenging scheduling problems in Cloud data centers is to take the allocation and migration of reconfigurable virtual machines as well as the integrated features of hosting physical machines into consideration. We introduce a Dynamic and Integrated Resource Scheduling algorithm (DAIRS) for Cloud data centers. Unlike traditional load-balance scheduling algorithms which often consider only one factor such as the CPU load in physical servers, DAIRS treats CPU, memory and network bandwidth integrated for both physical machines and virtual machines. We develop integrated measurement for the total imbalance level of a Cloud datacenter as well as the average imbalance level of each server. Simulation results show that DAIRS has good performance with regard to total imbalance level, average imbalance level of each server, as well as overall running time.
基金supported in part by the Major Program of the National Natural Science Foundation of China(62495021 and 62495020).
文摘The rapid growth of low-Earth-orbit satellites has injected new vitality into future service provisioning.However,given the inherent volatility of network traffic,ensuring differentiated quality of service in highly dynamic networks remains a significant challenge.In this paper,we propose an online learning-based resource scheduling scheme for satellite-terrestrial integrated networks(STINs)aimed at providing on-demand services with minimal resource utilization.Specifically,we focus on:①accurately characterizing the STIN channel,②predicting resource demand with uncertainty guarantees,and③implementing mixed timescale resource scheduling.For the STIN channel,we adopt the 3rd Generation Partnership Project channel and antenna models for non-terrestrial networks.We employ a one-dimensional convolution and attention-assisted long short-term memory architecture for average demand prediction,while introducing conformal prediction to mitigate uncertainties arising from burst traffic.Additionally,we develop a dual-timescale optimization framework that includes resource reservation on a larger timescale and resource adjustment on a smaller timescale.We also designed an online resource scheduling algorithm based on online convex optimization to guarantee long-term performance with limited knowledge of time-varying network information.Based on the Network Simulator 3 implementation of the STIN channel under our high-fidelity satellite Internet simulation platform,numerical results using a real-world dataset demonstrate the accuracy and efficiency of the prediction algorithms and online resource scheduling scheme.
基金Project(BK20201162)supported by the General Program of Natural Science Foundation of Jiangsu Province,ChinaProject(JC2019126)supported by the Science and Technology Plan Fundamental Scientific Research Funding Project of Nantong,China+1 种基金Project(CE20205045)supported by the Changzhou Science and Technology Support Plan(Social Development),ChinaProject(51875171)supported by the National Nature Science Foundation of China。
文摘In view of the fact that traditional job shop scheduling only considers a single factor, which affects the effect of resource allocation, the dual-resource integrated scheduling problem between AGV and machine in intelligent manufacturing job shop environment was studied. The dual-resource integrated scheduling model of AGV and machine was established by comprehensively considering constraints of machines, workpieces and AGVs. The bidirectional single path fixed guidance system based on topological map was determined, and the AGV transportation task model was defined. The improved A* path optimization algorithm was used to determine the optimal path, and the path conflict elimination mechanism was described. The improved NSGA-Ⅱ algorithm was used to determine the machining workpiece sequence, and the competition mechanism was introduced to allocate AGV transportation tasks. The proposed model and method were verified by a workshop production example, the results showed that the dual resource integrated scheduling strategy of AGV and machine is effective.
基金This work is supported by the National Science Foundation of China under Grant No.F020803,and No.61602254the National Science Foundation of Jiangsu Province,China,under Grant No.BK20160968the Project through the Priority Academic Program Development(PAPD)of Jiangsu Higher Education Institutions,the China-USA Computer Science Research Center.
文摘Nowadays,emergency accidents could happen at any time.The accidents occur unpredictably and the accidents requirements are diversely.The accidents happen in a dynamic environment and the resource should be cooperative to solve the accidents.Most methods are focusing on minimizing the casualties and property losses in a static environment.However,they are lack in considering the dynamic and unpredictable event handling.In this paper,we propose a representative environmental model in representation of emergency and dynamic resource allocation model,and an adaptive mathematical model based on Genetic Algorithm(GA)to generate an optimal set of solution domain.The experimental results show that the proposed algorithm can get a set of better candidate solutions.
基金supported by the National Natural Science Foundation of China (60879024)
文摘Recently the integrated modular avionics （IMA） architecture which introduces the concept of resource partitioning becomes popular as an alternative to the traditional federated architecture. A novel hierarchical approach is proposed to solve the resource allocation problem for IMA systems in distributed environments. Firstly, the worst case response time of tasks with arbitrary deadlines is analyzed for the two-level scheduler. Then, the hierarchical resource allocation approach is presented in two levels. At the platform level, a task assignment algorithm based on genetic simulated annealing （GSA） is proposed to assign a set of pre-defined tasks to different processing nodes in the form of task groups, so that resources can be allocated as partitions and mapped to task groups. While yielding to all the resource con- straints, the algorithm tries to find an optimal task assignment with minimized communication costs and balanced work load. At the node level, partition parameters are optimized, so that the computational resource can be allocated further. An example is shown to illustrate the hierarchal resource allocation approach and manifest the validity. Simulation results comparing the performance of the proposed GSA with that of traditional genetic algorithms are presented in the context of task assignment in IMA systems.
基金This work was supported in part by the National Natural Science Foundation of China(No.62373380).
文摘The practical engineering of satellite tracking telemetry and command(TT&C)is often disturbed by unpredictable external factors,including the temporary rise in a significant quantity of satellite TT&C tasks,temporary failures and failures of some TT&C resources,and so on.To improve the adaptability and robustness of satellite TT&C systems when faced with uncertain dynamic disturbances,a hierarchical disturbance propagation mechanism and an improved contract network dynamic scheduling method for satellite TT&C resources were designed to address the dynamic scheduling problem of satellite TT&C resources.Firstly,the characteristics of the dynamic scheduling problem of satellite TT&C resources are analyzed,and a mathematical model is established with the weighted optimization objectives of maximizing the revenue from task completion and minimizing the degree of plan disturbance.Then,a bottom-up distributed dynamic collaborative scheduling framework for satellite TT&C resources is proposed,which includes a task layer,a resource layer,a central internal collaboration layer,and a central external collaboration layer.Dynamic disturbances are propagated layer by layer from the task layer to the central external collaboration layer in a bottom-up manner,using efficient heuristic strategies in the task layer and the resource layer,respectively.We use improved contract network algorithms in the center internal collaboration layer and the center external collaboration layer,the original scheduling plan is quickly adjusted to minimize the impact of disturbances while effectively completing dynamic task requirements.Finally,a large number of simulation experiments were carried out and compared with various comparative algorithms.The results show that the proposed algorithm can effectively improve the solution effect of satellite TT&C resource dynamic scheduling problems,and has good application prospects.
文摘近年来,网络功能虚拟化(NFV)以其网络设备功能解耦和无缝交互等优势,逐步成为现代网络设计的核心技术。其中,SD-WAN(Software Defined Wide Area Network)以其可编程性和灵活性,为NFV应用的场景提供了广阔的空间。文中以SD-WAN实际应用为背景,探讨了NFV在其中的作用和优化策略。首先,建立了一个SD-WAN环境,采用网络功能虚拟化技术,实现了如防火墙,负载均衡等核心网络功能的动态配置和部署。实验结果表明,相对于传统的物理设备,NFV技术在不影响网络性能的同时,降低了设备成本和维护成本。然后,针对SD-WAN的特点,提出了一种资源调度优化算法,其能根据实时网络状况,动态调整虚拟网络功能的资源分配,从而进一步提高其性能。通过实验证明,该优化策略可有效提升整体网络的灵活性、稳定性和效能,这为SD-WAN的实际应用场景提供了有效的优化策略参考,有助于推动NFV在SD-WAN等宽域网络中的进一步应用。
