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International Journal of Control and Automation 2015年第11期8卷 325-336页

作者： Ren, Yongjian Ye, Jiaolong Zhang, Jilin Zhou, Li Wang, Jue Zhang, Lei School of Computer Science and Technology Hangzhou Dianzi University Hangzhou China Key Laboratory of Complex Systems Modeling and Simulation Ministry of Education China College of Electrical Engineering Zhejiang University Hangzhou China Supercomputing Center of Computer Network Information Center Chinese Academy of Sciences Beijing China Computer Science Department Beijing University of Civil Engineering and Architecture Beijing China

The OraCDP disaster recovery system uses CDP disaster recovery technology based on the combination of block level, combining with the communication coupling between the underlying I/O and Oracle database. The experimental results show that the OraCDP system can not only maintain the normal operation of the original system without any negative influence, but also guarantee the recovery of data and service at specific time quickly, fully and accurately. © 2015 SERSC.

关键词： Recovery

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An efficient storage technology for object-based distributed storage system

International Journal of Control and Automation

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International Journal of Control and Automation 2015年第11期8卷 337-348页

作者： Zhang, Jilin Su, Yucheng Wan, Jian Zhou, Li Wang, Jue Zhang, Lei College of Electrical Engineering Zhejiang University Hangzhou China School of Computer Science and Technology Hangzhou Dianzi University Hangzhou China Key Laboratory of Complex Systems Modeling and Simulation Ministry of Education China Supercomputing Center of Computer Network Information Center Chinese Academy of Sciences Beijing China Computer Science Department Beijing University of Civil Engineering and Architecture Beijing China

There have two effective ways to improve the overall efficiency of the object-based distributed storage system, one is network caching technology and the other is metadata server cluster load balancing strategy. Under the heterogeneous storage environments, object-based distributed file system face the key challenge of lacking caching mechanism for the high-frequency access files, metadata server load imbalance also reduce the overall efficiency. To address these challenges, we discuss the design and implementation of an object-based distributed file storage caching system, and propose a weight-based metadata server cluster load balancing strategy. It effectively improve the metadata processing capacity. Based on the results, it demonstrated the feasibility and the efficiency of our methods. © 2015 SERSC.

关键词： Metadata

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Virtual Page Behavior Based Page Management Policy for Hybrid Main Memory in Cloud Computing 12

Virtual Page Behavior Based Page Management Policy for Hybri...

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12th International Conference on Mobile Ad-Hoc and Sensor Networks, MSN 2016

作者： Huang, Jie Zhang, Xuan Han, Guangjie Jia, Gangyong Liyou, Huizi Wan, Jian Department of Computer Science and Technology Hangzhou Dianzi University Hangzhou310018 China Key Laboratory of Complex Systems Modeling and Simulation Ministry of Education Hangzhou310018 China Department of Information and Communication Systems Hohai University Changzhou213022 China School of Information and Electronic Engineering Zhejiang University of Science and Technology Hangzhou310023 China

ISBN: (纸本)9781509056965

A new generation memory, Non-Volatile Memory (NVM), such as Phase-Change Memory (PCM), has been adopted together with DRAM in the main memory to form the hybrid main memory for low energy consumption and high capacity. The biggest challenge of hybrid memory is how to decrease the average memory access cost for the higher cost of NVM's read/write operation. Currently, most researches are based on migration. However, the page migration itself is a high cost operation. And the migration based policy produces many migration operations, which induces high cost in memory access. Therefore, in order to decrease the cost, we present a virtual page behavior based page management policy (VBPM) in this paper. According to the virtual pages' behavior, we allocate virtual pages into DRAM or PCM physical pages correspondingly. The whole process is migration independent. The experimental results show our VBPM decreases the average memory access time by 24%, moreover, VBPM improves real-time performance in critical path. © 2016 IEEE.

关键词： Phase change memory

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BPaaS: A platform for artifact-centric business process customization in cloud computing 29

BPaaS: A platform for artifact-centric business process cust...

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29th International Conference on Software Engineering and Knowledge Engineering, SEKE 2017

作者： Gao, Min Yin, Yu Wang, Xingfei Li, Ying Chen, Zaidie Guo, Lipeng Key Laboratory of Complex Systems Modeling and Simulation of Ministry of Education College of Electrical Engineering Hangzhou Dianzi University Zhejiang China College of Computer Science Zhejiang University Zhejiang Hangzhou China College of Computer Science Fudan University Shanghai China Hangzhou Housing Management Bureaus Hangzhou Zhejiang China

ISBN: (纸本)1891706411

As a new service paradigm of Software-As-A-Service (SaaS),Business Process-As-A-Service (BPaaS). BPaaS is used to build a cost-effective Business Process Management (BPM) system. Based on universal Artifacts, we develop a framework named SeGA (Self-Guided Artifact). In SeGA, a BPM system is capable of executing business processes from multiple clients, and responding query at runtime. what's more, by the template-based cascading data mapping method, entity to be synchronized with database automatically, so each BP instance can modify its process entity without worrying about the database access. In this paper, we conduct a deep research and implement a prototype system for Artifact process design.

关键词： Process design

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A Client Selection Method Based on Loss Function Optimization for Federated Learning

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Computer modeling in Engineering & Sciences 2023年第10期137卷 1047-1064页

作者： Yan Zeng Siyuan Teng Tian Xiang Jilin Zhang Yuankai Mu Yongjian Ren Jian Wan School of Computer Science and Technology Hangzhou Dianzi UniversityHangzhou310018China Key Laboratory of Complex System Modeling and Simulation Ministry of EducationHangzhou310018China Zhejiang Engineering Research Center of Data Security Governance Hangzhou310018China Intelligent Robotics Research Center Zhejiang LabHangzhou311100China HDU-ITMO Joint Institute Hangzhou Dianzi UniversityHangzhou310018China

Federated learning is a distributedmachine learningmethod that can solve the increasingly serious problemof data islands and user data privacy,as it allows training data to be kept locally and not shared with other *** trains a globalmodel by aggregating locally-computedmodels of clients rather than their ***,the divergence of local models caused by data heterogeneity of different clients may lead to slow convergence of the global *** this problem,we focus on the client selection with federated learning,which can affect the convergence performance of the global model with the selected local *** propose FedChoice,a client selection method based on loss function optimization,to select appropriate local models to improve the convergence of the global *** firstly sets selected probability for clients with the value of loss function,and the client with high loss will be set higher selected probability,which can make them more likely to participate in ***,it introduces a local control vector and a global control vector to predict the local gradient direction and global gradient direction,respectively,and calculates the gradient correction vector to correct the gradient direction to reduce the cumulative deviationof the local gradient causedby *** experiments to verify the validity of FedChoice on CIFAR-10,CINIC-10,MNIST,EMNITS,and FEMNIST datasets,and the results show that the convergence of FedChoice is significantly improved,compared with FedAvg,FedProx,and FedNova.

关键词： Federated learning model aggregation Non-IID

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FedAG:A Federated Learning Method Based on Data Importance Weighted Aggregation

FedAG:A Federated Learning Method Based on Data Importance W...

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2023 IEEE/CIC International Conference on Communications in China, ICCC 2023

作者： Xu, Mengchu Zeng, Yan Xue, Meiting Zhang, Ji-Lin Wan, Jian Zhou, Mingyao Wen, Yilin Shi, Yukun Hangzhou Dianzi University School of Computer Science and Technology Hangzhou China Key Laboratory of Complex Systems Modeling and Simulation Ministry of Education Hangzhou China Zhejiang Engineering Research Center of Data Security Governance Hangzhou China Hangzhou Dianzi University School of Cyberspace Hangzhou China Huawei Enterprise Communication Technology Co Hangzhou China

ISBN: (纸本)9798350345384

Federated learning is a distributed machine learning approach that trains models with multiple clients and data locally. However, the existing methods ignore the differences between local models caused by the data heterogeneity, and give a high aggregation weight for the low-quality local model, which leads to low accuracy of the global model. For this problem, we propose a federated learning method based on data importance weighted aggregation, FedAG. It constructs an evaluation model of data importance based on the data distribution skewness, data volume, and data quality of clients, and aggregates local models with different weights computed by the evaluation model of data importance into a global model. We make experiments on five datasets including EMNIST, MNIST, and CIFAR-10. The results show that the accuracy of FedAG is respectively improved by 6.5%, 1.8%, 1.3% and 2.1%, compared with FedAvg, FedProx, FedVar, and Scaffold algorithms. © 2023 IEEE.

关键词： Scaffolds

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BthyDra+: Towards a Comprehensive Model to Conduct Cross-project Defect Prediction

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Journal of Computers (Taiwan) 2018年第6期29卷 52-65页

作者： Huang, Ning Fang, Jinglong Wei, Dan Chen, Bin Wang, Xingqi School of Computer Science Hangzhou Dianzi University ZheJiang Province China Key Laboratory of Complex Systems Modeling and Simulation Ministry of Education School of Computer Science Hangzhou Dianzi University ZheJiang Province China

Cross-project defect prediction (CPDP) is a field of study where researchers need to build a universal model by using within-project data to predict defects on other projects. However, variations in the distribution of source and target projects have an influence on the performance of classifiers. To enable effective cross-project defect prediction, we propose a comprehensive model containing data preprocessing and classifier transferring to construct a better classification space and strengthen the performance of classifiers. In preprocessing step, one baseline is calculated for every dataset from its non-defective samples based on the distance to all other non-defective samples and the data is transformed by using rank function. Genetic algorithm and ensemble learning are selected as the way in transferring step to extract effective representation from source projects and boost the capability of weak classifiers. We use Naive Bayes, Support Vector Machine and Classification and Regression Trees as classifiers and apply this model on five open resource projects (one Apache and four Eclipse projects) and NASA MDP dataset. Selecting accuracy as fitness in genetic algorithm improves the performance of classification. The model we proposed yields similar results and obtains higher precision comparing the within-project models. Meanwhile, it obtains better performance than the state-of-the-art methods on cross-project defect prediction. These results show that our model provides an opportunity to training classifiers by using more samples from different projects. © 2018 Computer Society of the Republic of China. All rights reserved.

关键词： Genetic algorithms

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Design and implementation of multiple volume servers block level storage system based on load-balanced strategy

International Journal of Database Theory and Application

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International Journal of Database Theory and Application 2014年第4期7卷 59-78页

作者： Wan, Jian Chen, Xun You, Xindong School of Computer Science and Technology Hangzhou Dianzi University Hangzhou China Key Laboratory of Complex System Modeling and Simulation Ministry of Education China

Block level storage system has been widely used as it can provide users raw block device. On the basis of Orthrus system, this paper designs and implements a multiple volume servers block level storage system based on load-balanced strategy-Orthrus Plus. This system uses the dynamic load-balanced strategy based on genetic algorithm strategy to load balance the volume servers clusters and proposes an iSCSI pause and resume method to solve the breakpoint retransmission problem during load-balancing. At last, we design a hierarchical management mechanism based on volume life cycle at storage. Experiments show that the load balancing capability in Orthrus Plus is more accurate and efficient under the situation of larger amount of data, and the hierarchical storage strategy also increases the I/O throughout capacity. © 2013 SERSC.

关键词： Genetic algorithms

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Statistics of active and passive scalars in one-dimensional compressible turbulence

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Physical Review E 2012年第6期86卷 066307-066307页

作者： Qionglin Ni Shiyi Chen State Key Laboratory of Turbulence and Complex Systems Center for Applied Physics and Technology and Key Laboratory of High Energy Density Physics Simulation Ministry of Education College of Engineering Peking University 100871 Beijing People's Republic of China

Statistics of the active temperature and passive concentration advected by the one-dimensional stationary compressible turbulence at Reλ=2.56×106 and Mt=1.0 is investigated by using direct numerical simulation with all-scale forcing. It is observed that the signal of velocity, as well as the two scalars, is full of small-scale sawtooth structures. The temperature spectrum corresponds to G(k)∝k−5/3, whereas the concentration spectrum acts as a double power law of H(k)∝k−5/3 and H(k)∝k−7/3. The probability distribution functions (PDFs) for the two scalar increments show that both δT and δC are strongly intermittent at small separation distance r and gradually approach the Gaussian distribution as r increases. Simultaneously, the exponent values of the PDF tails for the large negative scalar gradients are qθ=−4.0 and qζ=−3.0, respectively. A single power-law region of finite width is identified in the structure function (SF) of δT; however, in the SF of δC, there are two regions with the exponents taken as a local minimum and a local maximum. As for the scalings of the two SFs, they are close to the Burgers and Obukhov-Corrsin scalings, respectively. Moreover, the negative filtered flux at large scales and the time-increasing total variance give evidences to the existence of an inverse cascade of the passive concentration, which is induced by the implosive collapse in the Lagrangian trajectories.

关键词： TURBULENCE TEMPERATURE COMPUTER simulation GAUSSIAN distribution LAGRANGIAN functions TRAJECTORIES (Mechanics) POWER law (Mathematics)

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Decadal climate variability during the pre-industrial Common Era: characteristics and mechanisms

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Science Bulletin 2025年

作者： Liang Ning Zhengyu Liu Michael E. Mann Jian Liu Mi Yan Weiyi Sun Kefan Chen Yanmin Qin Qin Wen Key Laboratory for Virtual Geographic Environment Ministry of Education Nanjing 210023 China State Key Laboratory Cultivation Base of Geographical Environment Evolution and Regional Response of Jiangsu Province Nanjing 210023 China Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application Nanjing 210023 China School of Geography Nanjing Normal University Nanjing 210023 China Department of Geography The Ohio State University Columbus OH 43210 USA Department of Earth and Environmental Science Annenberg School for Communication University of Pennsylvania Philadelphia PA 19104 USA Jiangsu Provincial Key Laboratory for Numerical Simulation of Large Scale Complex Systems School of Mathematical Science Nanjing Normal University Nanjing 210023 China

In this article, we present a comprehensive review of decadal to multi-decadal climate variability during the Common Era (CE), focusing on their characteristics and mechanisms. We begin by summarizing recent advances in proxy reconstructions that reveal the paleo-evidence of decadal to multi-decadal climate variability during the CE. Decadal to multi-decadal variability has been observed in extensive sets of proxy records in the CE. Despite improvements in proxy records in the type, temporal resolution, and temporal coverage, there remains a lack of clear consistency in the preferred time scales and phases of the variability among different records. The agreements of decadal characteristics between proxy records and model simulations are higher during the periods with strong external forcings, but lower during periods of weak external forcing. We subsequently describe the recent modeling studies on the influences of external forcings and internal variability on decadal to multi-decadal climate variability with associated physical mechanisms, and some emerging research topics. Despite the improved understanding of climate variability and regional climate changes, especially over the eastern Asia summer monsoon region, several inconsistencies still exist, such as the amplitudes of responses to external forcings and relative contributions from external forcings and internal variability. The review ends with perspectives for future directions to reconcile discrepancies of decadal climate variability, such as applications of paleoclimate data assimilation and isotope-enabled transient climate modeling, and implications for projecting future decadal to multi-decadal climate changes and for improving the accuracy of decadal predictions.

关键词： Decadal climate variability External forcings Internal variability Pre-industrial Common Era

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