How to effectively reduce the energy consumption of large-scale data centers is a key issue in cloud computing. This paper presents a novel low-power task scheduling algorithm （L3SA） for large-scale cloud data cente...How to effectively reduce the energy consumption of large-scale data centers is a key issue in cloud computing. This paper presents a novel low-power task scheduling algorithm （L3SA） for large-scale cloud data centers. The winner tree is introduced to make the data nodes as the leaf nodes of the tree and the final winner on the purpose of reducing energy consumption is selected. The complexity of large-scale cloud data centers is fully consider, and the task comparson coefficient is defined to make task scheduling strategy more reasonable. Experiments and performance analysis show that the proposed algorithm can effectively improve the node utilization, and reduce the overall power consumption of the cloud data center.展开更多
This paper considers a time-constrained data collection problem from a network of ground sensors located on uneven terrain by an Unmanned Aerial Vehicle(UAV),a typical Unmanned Aerial System(UAS).The ground sensors ha...This paper considers a time-constrained data collection problem from a network of ground sensors located on uneven terrain by an Unmanned Aerial Vehicle(UAV),a typical Unmanned Aerial System(UAS).The ground sensors harvest renewable energy and are equipped with batteries and data buffers.The ground sensor model takes into account sensor data buffer and battery limitations.An asymptotically globally optimal method of joint UAV 3D trajectory optimization and data transmission schedule is developed.The developed method maximizes the amount of data transmitted to the UAV without losses and too long delays and minimizes the propulsion energy of the UAV.The developed algorithm of optimal trajectory optimization and transmission scheduling is based on dynamic programming.Computer simulations demonstrate the effectiveness of the proposed algorithm.展开更多
A hybrid scheduling algorithm based on genetic algorithm is proposed in this paper for reconnaissance satellite data transmission.At first,based on description of satellite data transmission request,satellite data tra...A hybrid scheduling algorithm based on genetic algorithm is proposed in this paper for reconnaissance satellite data transmission.At first,based on description of satellite data transmission request,satellite data transmission task model and satellite data transmission scheduling problem model are established.Secondly,the conflicts in scheduling are discussed.According to the meaning of possible conflict,the method to divide possible conflict task set is given.Thirdly,a hybrid algorithm which consists of genetic algorithm and heuristic information is presented.The heuristic information comes from two concepts,conflict degree and conflict number.Finally,an example shows the algorithm's feasibility and performance better than other traditional展开更多
随着新一代信息通信技术,如5G、云计算和人工智能的不断演进,世界正迅速迈入数字经济的快车道。针对数据中心中可再生能源和工作负载预测的不确定性,提出了一种基于多智能体近端策略网络的数据中心双层优化调度方法。首先,建立了数据中...随着新一代信息通信技术,如5G、云计算和人工智能的不断演进,世界正迅速迈入数字经济的快车道。针对数据中心中可再生能源和工作负载预测的不确定性,提出了一种基于多智能体近端策略网络的数据中心双层优化调度方法。首先,建立了数据中心双层时空优化调度框架,对数据中心工作负载、IT设备、空调设备进行详细建模;在此基础上,提出数据中心的双层优化调度模型,上层以互联网数据中心(Internet data center,IDC)运营管理商总运营成本最小为目标进行时间维度调度,下层以各IDC运行成本最低为目标进行空间维度调度;然后,介绍多智能体近端策略网络算法原理,设计数据中心双层优化调度模型的状态空间、动作空间和奖励函数。最后,针对算例进行离线训练和在线调度决策,仿真结果表明,所提模型和方法能够有效降低系统成本和能耗,实现工作负载的最佳分配,具有较好的经济性和鲁棒性。展开更多
基金supported by the National Natural Science Foundation of China(6120200461272084)+9 种基金the National Key Basic Research Program of China(973 Program)(2011CB302903)the Specialized Research Fund for the Doctoral Program of Higher Education(2009322312000120113223110003)the China Postdoctoral Science Foundation Funded Project(2011M5000952012T50514)the Natural Science Foundation of Jiangsu Province(BK2011754BK2009426)the Jiangsu Postdoctoral Science Foundation Funded Project(1102103C)the Natural Science Fund of Higher Education of Jiangsu Province(12KJB520007)the Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions(yx002001)
文摘How to effectively reduce the energy consumption of large-scale data centers is a key issue in cloud computing. This paper presents a novel low-power task scheduling algorithm （L3SA） for large-scale cloud data centers. The winner tree is introduced to make the data nodes as the leaf nodes of the tree and the final winner on the purpose of reducing energy consumption is selected. The complexity of large-scale cloud data centers is fully consider, and the task comparson coefficient is defined to make task scheduling strategy more reasonable. Experiments and performance analysis show that the proposed algorithm can effectively improve the node utilization, and reduce the overall power consumption of the cloud data center.
基金funding from the Australian Government,via Grant No.AUSMURIB000001 associated with ONR MURI Grant No.N00014-19-1-2571。
文摘This paper considers a time-constrained data collection problem from a network of ground sensors located on uneven terrain by an Unmanned Aerial Vehicle(UAV),a typical Unmanned Aerial System(UAS).The ground sensors harvest renewable energy and are equipped with batteries and data buffers.The ground sensor model takes into account sensor data buffer and battery limitations.An asymptotically globally optimal method of joint UAV 3D trajectory optimization and data transmission schedule is developed.The developed method maximizes the amount of data transmitted to the UAV without losses and too long delays and minimizes the propulsion energy of the UAV.The developed algorithm of optimal trajectory optimization and transmission scheduling is based on dynamic programming.Computer simulations demonstrate the effectiveness of the proposed algorithm.
文摘A hybrid scheduling algorithm based on genetic algorithm is proposed in this paper for reconnaissance satellite data transmission.At first,based on description of satellite data transmission request,satellite data transmission task model and satellite data transmission scheduling problem model are established.Secondly,the conflicts in scheduling are discussed.According to the meaning of possible conflict,the method to divide possible conflict task set is given.Thirdly,a hybrid algorithm which consists of genetic algorithm and heuristic information is presented.The heuristic information comes from two concepts,conflict degree and conflict number.Finally,an example shows the algorithm's feasibility and performance better than other traditional
文摘随着新一代信息通信技术,如5G、云计算和人工智能的不断演进,世界正迅速迈入数字经济的快车道。针对数据中心中可再生能源和工作负载预测的不确定性,提出了一种基于多智能体近端策略网络的数据中心双层优化调度方法。首先,建立了数据中心双层时空优化调度框架,对数据中心工作负载、IT设备、空调设备进行详细建模;在此基础上,提出数据中心的双层优化调度模型,上层以互联网数据中心(Internet data center,IDC)运营管理商总运营成本最小为目标进行时间维度调度,下层以各IDC运行成本最低为目标进行空间维度调度;然后,介绍多智能体近端策略网络算法原理,设计数据中心双层优化调度模型的状态空间、动作空间和奖励函数。最后,针对算例进行离线训练和在线调度决策,仿真结果表明,所提模型和方法能够有效降低系统成本和能耗,实现工作负载的最佳分配,具有较好的经济性和鲁棒性。
