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A Survey and Experimental Review on data distribution Strategies for Parallel Spatial Clustering Algorithms

Journal of Computer Science & Technology 2024年第3期39卷 610-636页

作者： Jagat Sesh Challa Navneet Goyal Amogh Sharma Nikhil Sreekumar Sundar Balasubramaniam Poonam Goyal Advanced data Analytics and Parallel Technologies Laboratory Birla Institute of Technology and Science Pilani 333031India Uber New York 11101U.S.A. Computer Science and Engineering Department University of MinnesotaMinneapolis 55455U.S.A.

The advent of Big data has led to the rapid growth in the usage of parallel clustering algorithms that work over distributed computing frameworks such as MPI,MapReduce,and *** important step for any parallel clustering algorithm is the distribution of data amongst the cluster *** step governs the methodology and performance of the entire *** typically use random,or a spatial/geometric distribution strategy like kd-tree based partitioning and grid-based partitioning,as per the requirements of the ***,these strategies are generic and are not tailor-made for any specific parallel clustering *** this paper,we give a very comprehensive literature survey of MPI-based parallel clustering algorithms with special reference to the specific data distribution strategies they *** also propose three new data distribution strategies namely Parameterized Dimensional Split for parallel density-based clustering algorithms like DBSCAN and OPTICS,Cell-Based Dimensional Split for dGridSLINK,which is a grid-based hierarchical clustering algorithm that exhibits efficiency for disjoint spatial distribution,and Projection-Based Split,which is a generic distribution *** of these preserve spatial locality,achieve disjoint partitioning,and ensure good data load *** experimental analysis shows the benefits of using the proposed data distribution strategies for algorithms they are designed for,based on which we give appropriate recommendations for their usage.

关键词： parallel data mining data distribution parallel clustering spatial locality preservation

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PAIDD:a hybrid P2P-based architecture for improving data distribution in social networks

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Science China(Information Sciences) 2014年第4期57卷 96-106页

作者： SHUANG Kai SU Sen State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications

Rapid growth in social networks(SNs)presents a unique scalability challenge for SN operators because of the massive amounts of data distribution among large number of concurrent online users.A request from any user may trigger hundreds of server activities to generate a customized page and which has already become a huge *** on the theoretical model and analytical study considering realistic network scenarios,this article proposes a hybrid P2P-based architecture called *** fulfills effective data distribution primarily through P2P connectivity and social graph among users but with the help of central *** increase system efficiency,PAIDD performs optimized content prefetching based on social interactions among *** chooses interaction as the criteria because user’s interaction graph is measured to be much smaller than the social *** experiments confirm that PAIDD ensures satisfactory user experience without incurring extensive overhead on clients’*** importantly,PAIDD can effectively achieve one order of magnitude of load reduction at central servers.

关键词： social network data distribution PAIDD hybrid P2P-based interaction-oriented

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Load-balancing data distribution in publish/subscribe mode

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Journal of Southeast University(English Edition) 2014年第4期30卷 428-433页

作者：李凯汪芸殷奕袁飞飞东南大学计算机科学与工程学院南京211189 东南大学教育部计算机网络与信息集成重点实验室南京211189 南京师范大学计算机与技术学院南京210046

To improve data distribution efficiency a load-balancing data distribution LBDD method is proposed in publish/subscribe *** the LBDD method subscribers are involved in distribution tasks and data transfers while receiving data themselves.A dissemination tree is constructed among the subscribers based on MD5 where the publisher acts as the root. The proposed method provides bucket construction target selection and path updates furthermore the property of one-way dissemination is *** the average out-going degree of a node is 2 is guaranteed with the proposed *** experiments on data distribution delay data distribution rate and load distribution are conducted. Experimental results show that the LBDD method aids in shaping the task load between the publisher and subscribers and outperforms the point-to-point approach.

关键词： data distribution publish/subscribe mode load balance dissemination tree

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Supporting Flexible data distributionin Software DSMs

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Journal of Computer Science & Technology 2000年第5期15卷 445-452页

作者：洪锦伟陈国良张兆庆 DepartmentofComputerScience UniversityofScienceandTechnologyofChinaHefei230027P.R.China

Page-based software DSM systems suffer from false sharing caused by the large sharing granularity, and only support one-dimension Block or Cyclicblock data distribution schemes. Thus applications running on them will suffer from poor data locality and will be able to exploit parallelism only when using a large number of processors. In this paper, a way towards supporting flexible data distribution (FDD) on software DSM system is presented. Small granularity-tunable blocks, the size of which can be set by compiler or programmer, are used to overlap the working data sets distributed among processors. The FDD was implemented on a software DSM system called JIAJIA. Compared with Block/Cyclic-block distribution schemes used by most DSM systems now, experiments show that the proposed way of flexible data distribution is more effective. The performance of the applications used in the experiments is significantly improved.

关键词： DSM JIAJIA data distribution address computation Dawning

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MBA:A market-based approach to data allocation and dynamic migration for cloud database

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Science China(Information Sciences) 2012年第9期55卷 1935-1948页

作者： HUANG Allen Microsoft SQL China R&D Center

With the coming shift to cloud computing,cloud database is emerging to provide database service over the *** the cloud-based environment,data are distributed at Internet scale and the system needs to handle a huge number of user queries simultaneously without *** data are distributed among the servers has a crucial impact on the query load distribution and the system response *** this paper,we propose a market-based control method,called MBA,to achieve query load balance via reasonable data *** MBA,database nodes are treated as traders in a market,and certain market rules are used to intelligently decide data allocation and *** built a prototype system and conducted extensive *** results show that the MBA method significantly improves system performance in terms of average query response time and fairness.

关键词： market-based control data distribution load balancing

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COMPILATION OF HEAT FLOW data IN THE CHINA CONTINENTAL AREA (2nd Edition)

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地震地质 1990年第4期 364-366页

作者： Wang Ji-yang and Huang Shao-peng(Institute of Geology, Academia Sinica, Beijing 100029)

During the last 2 years, heat flow data increased significantly in China as a result of implementation of many comprehensive geodynamic (including geothermal) projects and GGT project in China. In this paper, a total of 366 reliable heat flow data is collected from published and in press sources in the Compi-ilation of Heat Flow data in the China Continental Area (2nd edition). Statistic analysis of these data shows that the heat flow values in China continental area vary from 20 to 140 mWm-2. The mean value appears to be 66 mWm-2.

关键词： Heat flow data Quality category data distribution China continental area

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Federated Dynamic Client Selection for Fairness Guarantee in Heterogeneous Edge Computing

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Journal of Computer Science & Technology 2024年第1期39卷 139-158页

作者：毛莺池沈莉娟吴俊平萍吴杰 Key Laboratory of Water Big data Technology of Ministry of Water Resources Hohai UniversityNanjing 211100China College of Computer and Information Hohai UniversityNanjing 211100China Center of Networked Computing Temple UniversityPhiladelphiaPA 19122-6096U.S.A

Federated learning has emerged as a distributed learning paradigm by training at each client and aggregat-ing at a parameter *** heterogeneity hinders stragglers from responding to the server in time with huge com-munication *** client grouping in federated learning can solve the straggler problem,the stochastic selection strategy in client grouping neglects the impact of data distribution within each ***,current client grouping ap-proaches make clients suffer unfair participation,leading to biased performances for different *** order to guaran-tee the fairness of client participation and mitigate biased local performances,we propose a federated dynamic client selec-tion method based on data representativity(FedSDR).FedSDR clusters clients into groups correlated with their own lo-cal computational *** estimate the significance of client datasets,we design a novel data representativity evalua-tion scheme based on local data ***,the two most representative clients in each group are selected to optimize the global ***,the DYNAMIC-SELECT algorithm updates local computational efficiency and data representativity states to regroup clients after periodic average *** on real datasets show that FedS-DR improves client participation by 27.4%,37.9%,and 23.3%compared with FedAvg,TiFL,and FedSS,respectively,tak-ing fairness into account in federated *** addition,FedSDR surpasses FedAvg,FedGS,and FedMS by 21.32%,20.4%,and 6.90%,respectively,in local test accuracy variance,balancing the performance bias of the global model across clients.

关键词： federated learning fairness computational efficiency data distribution client selection client grouping

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A Two-Phase Paradigm for Joint Entity-Relation Extraction

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Computers, Materials & Continua 2023年第1期74卷 1303-1318页

作者： Bin Ji Hao Xu Jie Yu Shasha Li JunMa Yuke Ji Huijun Liu College of Computer National University of Defense TechnologyChangsha410073China The Affiliated Eye Hospital of Nanjing Medical University Nanjing210029China

An exhaustive study has been conducted to investigate span-based models for the joint entity and relation extraction ***,these models sample a large number of negative entities and negative relations during the model training,which are essential but result in grossly imbalanced data distributions and in turn cause suboptimal model *** order to address the above issues,we propose a two-phase paradigm for the span-based joint entity and relation extraction,which involves classifying the entities and relations in the first phase,and predicting the types of these entities and relations in the second *** two-phase paradigm enables our model to significantly reduce the data distribution gap,including the gap between negative entities and other entities,aswell as the gap between negative relations and other *** addition,we make the first attempt at combining entity type and entity distance as global features,which has proven effective,especially for the relation *** results on several datasets demonstrate that the span-based joint extraction model augmented with the two-phase paradigm and the global features consistently outperforms previous state-ofthe-art span-based models for the joint extraction task,establishing a new standard *** and quantitative analyses further validate the effectiveness the proposed paradigm and the global features.

关键词： Joint extraction span-based named entity recognition relation extraction data distribution global features

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A theoretical model for pattern discovery in visual analytics

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Visual Informatics 2021年第1期5卷 23-42页

作者： Natalia Andrienko Gennady Andrienko Silvia Miksch Heidrun Schumann Stefan Wrobel Fraunhofer Institute IAIS Sankt-AugustinGermany City University of LondonLondonUK TU Wien ViennaAustria University of Rostock RostockGermany University of Bonn BonnGermany

The word‘pattern’frequently appears in the visualisation and visual analytics literature,but what do we mean when we talk about patterns?We propose a practicable definition of the concept of a pattern in a data distribution as a combination of multiple interrelated elements of two or more data components that can be represented and treated as a unified *** theoretical model describes how patterns are made by relationships existing between data *** the types of these relationships,it is possible to predict what kinds of patterns may *** demonstrate how our model underpins and refines the established fundamental principles of *** model also suggests a range of interactive analytical operations that can support visual analytics workflows where patterns,once discovered,are explicitly involved in further data analysis.

关键词： Visual analytics data distribution Pattern Abstraction data organisation data arrangement data variation Pattern discovery

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Distributed Parallelization of a Global Atmospheric data Objective Analysis System

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Advances in Atmospheric Sciences 2003年第1期20卷 159-163页

作者：赵军宋君强李振军 College of Computer Science National University of Defense Technology Changsha 410073 Meteorological Center of Airforce Beijing100843

It is difficult to parallelize a subsistent sequential algorithm. Through analyzing the sequential algorithm of a Global Atmospheric data Objective Analysis System, this article puts forward a distributed parallel algorithm that statically distributes data on a massively parallel processing (MPP) computer. The algorithm realizes distributed parailelization by extracting the analysis boxes and model grid point Iatitude rows with leaped steps, and by distributing the data to different processors. The parallel algorithm achieves good load balancing, high parallel efficiency, and low parallel cost. Performance experiments on a MPP computer arc also presented.

关键词： distributed parailelization analysis box data distribution objective analysis

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