The distribution loads, output of distributed generations (DGs) and dynamic power price present obvious time-sequence property, the typical property is studied in this paper. The model of microgrid (including adjustab...The distribution loads, output of distributed generations (DGs) and dynamic power price present obvious time-sequence property, the typical property is studied in this paper. The model of microgrid (including adjustable load, DGs, storage and dynamic power price) is studied. A multi-timescale collaborative optimization model is built towards microgrid;main measures in different timescale optimization are realized. An improved adaptive genetic algorithm is used to solve the optimization problem, which improved the efficiency and reliability. The proposed optimization model is simulated in IEEE 33 node system;the results show it’s effective.展开更多
大地震能够同时激发出许多的地球自由振荡简正模,且地球的椭率、自转和内部的各向异性也会引起简正模的分裂,使各单线态之间的频率更接近(仅为几个μHz),这对地球自由振荡模型的检测提出更高的要求。本文以标准时频变换为基础,推导并验...大地震能够同时激发出许多的地球自由振荡简正模,且地球的椭率、自转和内部的各向异性也会引起简正模的分裂,使各单线态之间的频率更接近(仅为几个μHz),这对地球自由振荡模型的检测提出更高的要求。本文以标准时频变换为基础,推导并验证一种自由振荡模型检测的新方法。以3 S 1模型的检测为例,与经典的FT谱方法和最新的OSE方法相比,该方法具有更高的频率分辨率。展开更多
Workflow scheduling is a key issue and remains a challenging problem in cloud computing.Faced with the large number of virtual machine(VM)types offered by cloud providers,cloud users need to choose the most appropriat...Workflow scheduling is a key issue and remains a challenging problem in cloud computing.Faced with the large number of virtual machine(VM)types offered by cloud providers,cloud users need to choose the most appropriate VM type for each task.Multiple task scheduling sequences exist in a workflow application.Different task scheduling sequences have a significant impact on the scheduling performance.It is not easy to determine the most appropriate set of VM types for tasks and the best task scheduling sequence.Besides,the idle time slots on VM instances should be used fully to increase resources'utilization and save the execution cost of a workflow.This paper considers these three aspects simultaneously and proposes a cloud workflow scheduling approach which combines particle swarm optimization(PSO)and idle time slot-aware rules,to minimize the execution cost of a workflow application under a deadline constraint.A new particle encoding is devised to represent the VM type required by each task and the scheduling sequence of tasks.An idle time slot-aware decoding procedure is proposed to decode a particle into a scheduling solution.To handle tasks'invalid priorities caused by the randomness of PSO,a repair method is used to repair those priorities to produce valid task scheduling sequences.The proposed approach is compared with state-of-the-art cloud workflow scheduling algorithms.Experiments show that the proposed approach outperforms the comparative algorithms in terms of both of the execution cost and the success rate in meeting the deadline.展开更多
In orthogonal frequency division multiplexing （OFDM） systems, time and frequency synchronization are two critical elements for guaranteeing the orthogonality of OFDM subcarriers. Conventionally, with the employment ...In orthogonal frequency division multiplexing （OFDM） systems, time and frequency synchronization are two critical elements for guaranteeing the orthogonality of OFDM subcarriers. Conventionally, with the employment of pseudo-noise （PN） sequences in preamble design, the preamble information is not fully utilized in both symbol timing offset acquisition and carrier frequency offset estimation. In this article, a new synchronization algorithm is proposed for jointly optimizing the time and frequency synchronization. This algorithm uses polynomial sequences as synchronization preamble instead of PN sequences. Theoretical analysis and simulation results indicate that the proposed algorithm is much more accurate and reliable than other existing methods.展开更多
文摘The distribution loads, output of distributed generations (DGs) and dynamic power price present obvious time-sequence property, the typical property is studied in this paper. The model of microgrid (including adjustable load, DGs, storage and dynamic power price) is studied. A multi-timescale collaborative optimization model is built towards microgrid;main measures in different timescale optimization are realized. An improved adaptive genetic algorithm is used to solve the optimization problem, which improved the efficiency and reliability. The proposed optimization model is simulated in IEEE 33 node system;the results show it’s effective.
文摘大地震能够同时激发出许多的地球自由振荡简正模,且地球的椭率、自转和内部的各向异性也会引起简正模的分裂,使各单线态之间的频率更接近(仅为几个μHz),这对地球自由振荡模型的检测提出更高的要求。本文以标准时频变换为基础,推导并验证一种自由振荡模型检测的新方法。以3 S 1模型的检测为例,与经典的FT谱方法和最新的OSE方法相比,该方法具有更高的频率分辨率。
基金is with the School of Computing Science,Beijing University of Posts and Telecommunications,Beijing 100876,and also with the Key Laboratory of Trustworthy Distributed Computing and Service(BUPT),Ministry of Education,Beijing 100876,China(e-mail:zuoxq@bupt.edu.cn).supported in part by the National Natural Science Foundation of China(61874204,61663028,61703199)the Science and Technology Plan Project of Jiangxi Provincial Education Department(GJJ190959)。
文摘Workflow scheduling is a key issue and remains a challenging problem in cloud computing.Faced with the large number of virtual machine(VM)types offered by cloud providers,cloud users need to choose the most appropriate VM type for each task.Multiple task scheduling sequences exist in a workflow application.Different task scheduling sequences have a significant impact on the scheduling performance.It is not easy to determine the most appropriate set of VM types for tasks and the best task scheduling sequence.Besides,the idle time slots on VM instances should be used fully to increase resources'utilization and save the execution cost of a workflow.This paper considers these three aspects simultaneously and proposes a cloud workflow scheduling approach which combines particle swarm optimization(PSO)and idle time slot-aware rules,to minimize the execution cost of a workflow application under a deadline constraint.A new particle encoding is devised to represent the VM type required by each task and the scheduling sequence of tasks.An idle time slot-aware decoding procedure is proposed to decode a particle into a scheduling solution.To handle tasks'invalid priorities caused by the randomness of PSO,a repair method is used to repair those priorities to produce valid task scheduling sequences.The proposed approach is compared with state-of-the-art cloud workflow scheduling algorithms.Experiments show that the proposed approach outperforms the comparative algorithms in terms of both of the execution cost and the success rate in meeting the deadline.
基金supported by Korean Electronics and Telecommunications Research Institute,the Hi-Tech Research and Development Program of China(2006AA01Z283)the Natural Science Foundation of China(60772113)
文摘In orthogonal frequency division multiplexing （OFDM） systems, time and frequency synchronization are two critical elements for guaranteeing the orthogonality of OFDM subcarriers. Conventionally, with the employment of pseudo-noise （PN） sequences in preamble design, the preamble information is not fully utilized in both symbol timing offset acquisition and carrier frequency offset estimation. In this article, a new synchronization algorithm is proposed for jointly optimizing the time and frequency synchronization. This algorithm uses polynomial sequences as synchronization preamble instead of PN sequences. Theoretical analysis and simulation results indicate that the proposed algorithm is much more accurate and reliable than other existing methods.
