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A large scale power communication network simulation system based on big graph database

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Science China(Technological Sciences) 2019年第12期62卷 2088-2092页

作者： CHEN Jian JIANG Ying LU WenDa HAN Meng LI XiaoMing State Grid Zhejiang Electric Power Co Ltd.Hangzhou 310007China School of Computer Science and Engineering Nanjing University of Science&TechnologyNanjing 210094China Beijing Zhongdian Puhua Information Technology Co.LTD Beijing 100192China

The power communication network can be abstracted as a graph based on its topology. In this paper, we propose an approach to conduct simulations of power communication network based on its graph representation. In particular, the nodes and edges in the graph refer to the ports and channels in the grid topology. Different applications on the grid can be transformed into queries over the graph. Hence, in this paper, we build our grid simulation model based on the Neo4 j graph database. We also propose a fault extension algorithm based on predicate calculus. Our experiment evaluations show that the proposed approach can effectively improve the efficiency of the power grid.

关键词： power communication network graph database fault-spreading algorithm predicate calculus

Towards sparse matrix operations:graph database approach for power grid computation

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Global Energy Interconnection 2023年第1期6卷 50-63页

作者： Daoxing Li Kai Xiao Xiaohui Wang Pengtian Guo Yong Chen China Electric Power Research Institute Co.Ltd. Beijing 100192P.R.China

The construction of new power systems presents higher requirements for the Power Internet of Things(PIoT)***“source-grid-load-storage”architecture of a new power system requires PIoT to have a stronger multi-source heterogeneous data fusion *** graph databases have great advantages in dealing with multi-source heterogeneous data,which make them suitable for an increasing number of analytical computing ***,only few existing graph database products have native support for matrix operation-related interfaces or functions,resulting in low efficiency when handling matrix calculations that are commonly encountered in power *** this paper,the matrix computation process is expressed by a strategy called graph description,which relies on the natural connection between the matrix and structure of the *** on that,we implement matrix operations on graph database,including matrix multiplication,matrix decomposition,***,only the nodes relevant to the computation and their neighbors are concerned in the process,which prunes the influence of zero elements in the matrix and avoids useless iterations compared to the conventional matrix *** on the graph description,a series of power grid computations can be implemented on graph database,which reduces redundant data import and export operations while leveraging the parallel computing capability of graph *** promotes the efficiency of PIoT when handling multi-source heterogeneous *** comprehensive experimental study over two different scale power system datasets compares the proposed method with Python and MATLAB *** results reveal the superior performance of our proposed method in both power flow and N-1 contingency computations.

关键词： graph database graph description Matrix Parallel computing Power flow

Redesign of the gStore system

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Frontiers of Computer Science 2018年第4期12卷 623-641页

作者： Li ZENG Lei ZOU School of Electronics Engineering and Computer Science Peking University Beijing 100871 China Beijing Institute of Big Data Research Beijing 100871 China

gStore is an open-source native Resource Description Framework （RDF） triple store that answers SPARQL queries by subgraph matching over RDF graphs. However, there are some deficiencies in the original system design, such as answering simple queries （including one-triple pattern queries）. To improve the efficiency of the system, we reconsider the system design in this paper. Specifically, we propose a new query plan generation module that generates different query plans according to the structures of query graphs. Furthermore, we re-design our vertex encoding strategy to achieve more pruning power and a new multi-join algorithm to speed up the subgraph matching process. Extensive experiments on synthetic and real RDF datasets show that our method outperforms the state-of-the-art algorithms significantly.

关键词： graph database subgraph matching RDF management SPARQL query

Efficient Relational Techniques for Processing graph Queries

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Journal of Computer Science & Technology 2010年第6期25卷 1237-1255页

作者： Sherif Sakr Ghazi Al-Naymat School of Computer Science and Engineering University of New South Wales Managing Complexity Group National ICT Australia (NICTA)

graphs are widely used for modeling complicated data such as social networks,chemical compounds,protein interactions and semantic *** effiectively understand and utilize any collection of graphs,a graph database that efficiently supports elementary querying mechanisms is crucially *** example,Subgraph and Supergraph queries are important types of graph queries which have many applications in practice.A primary challenge in computing the answers of graph queries is that pair-wise comparisons of graphs are usually hard *** database management systems（RDBMSs） have repeatedly been shown to be able to efficiently host different types of data such as complex objects and XML *** derive much of their performance from sophisticated optimizer components which make use of physical properties that are specific to the relational model such as sortedness,proper join ordering and powerful indexing *** this article,we study the problem of indexing and querying graph databases using the relational *** present a purely relational framework for processing graph *** framework relies on building a layer of graph features knowledge which capture metadata and summary features of the underlying graph *** describe different querying mechanisms which make use of the layer of graph features knowledge to achieve scalable performance for processing graph ***,we conduct an extensive set of experiments on real and synthetic datasets to demonstrate the efficiency and the scalability of our techniques.

关键词： graph database graph query subgraph query supergraph query

Processes and events in the centre:a dynamic data model for representing spatial change

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International Journal of Digital Earth 2022年第1期15卷 276-295页

作者： Yufeng He Yehua Sheng Barbara Hofer Yi Huang Jiarui Qin School of Geography Nanjing Normal UniversityNanjingPeople’s Republic of China Key Laboratory of Virtual Geographic Environment (Nanjing Normal University) Ministry of EducationNanjingPeople’s Republic of China Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application NanjingPeople’s Republic of China Department of Geoinformatics-Z_GIS University of SalzburgSalzburgAustria School of Geographic and Biologic Information Nanjing University of Posts and TelecommunicationsNanjingPeople’s Republic of China

Traditional geographic information system models for map representation use superposition of layers to model physical reality,neglecting the integrity of the environment and limiting the ability to express interactions between features in complex *** results in limitations regarding dynamic simulation and geographic causality *** this paper,we extend the framework of the geographic scene by formalizing the relationship between geographic processes and events to construct a dynamic data model:the process-event-centred dynamic data *** key element of this data model is relationships between processes,events,and states of the natural or man-made phenomenon of *** identified relationships can be translated into a network of hierarchical,developmental,and causal graphs and realized in the Neo4j graph *** implementation in the graph database supports spatio-temporal reasoning in geographic scenes and achieves an organizational framework for simulating spatio-temporal dynamics and complex *** example of a 2019 mega-typhoon process is used to demonstrate the introduced process-event-centred model and its implementation in the graph database.A series of queries to the graph database show the capabilities of the data model for spatial reasoning and dynamic modeling.

关键词： Spatio-temporal dynamics geographic scene geographic processes geographic events spatio-temporal reasoning graph database

Building a High-Performance graph Storage on Top of Tree-Structured Key-Value Stores

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Big Data Mining and Analytics 2024年第1期7卷 156-170页

作者： Heng Lin Zhiyong Wang Shipeng Qi Xiaowei Zhu Chuntao Hong Wenguang Chen Yingwei Luo School of Computer Science Peking UniversityBeijing 100871China Ant Group Beijing 100020China Department of Computer Science and Technology Tsinghua UniversityBeijing 100084China

graph databases have gained widespread adoption in various industries and have been utilized in a range of applications,including financial risk assessment,commodity recommendation,and data lineage *** the principles and design of these databases have been the subject of some investigation,there remains a lack of comprehensive examination of aspects such as storage layout,query language,and *** present study focuses on the design and implementation of graph storage layout,with a particular emphasis on tree-structured key-value *** also examine different design choices in the graph storage layer and present our findings through the development of Tugraph,a highly efficient single-machine graph database that significantly outperforms well-known graph database Management System(GDBMS).Additionally,Tugraph demonstrates superior performance in the Linked Data Benchmark Council(LDBC)Social Network Benchmark(SNB)interactive benchmark.

关键词： graph database high-performance graph storage

Visualizing risk factors of dementia from scholarly literature using knowledge maps and next-generation data models

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Visual Computing for Industry,Biomedicine,and Art 2021年第1期4卷 165-182页

作者： Kiran Fahd Sitalakshmi Venkatraman Department of Information Technology Melbourne Polytechnic3181 PrahranVICAustralia

Scholarly communication of knowledge is predominantly document-based in digital repositories,and researchers find it tedious to automatically capture and process the semantics among related *** the present digital era of big data,there is a lack of visual representations of the knowledge present in scholarly articles,and a time-saving approach for a literature search and visual navigation is *** majority of knowledge display tools cannot cope with current big data trends and pose limitations in meeting the requirements of automatic knowledge representation,storage,and dynamic *** address this limitation,the main aim of this paper is to model the visualization of unstructured data and explore the feasibility of achieving visual navigation for researchers to gain insight into the knowledge hidden in scientific articles of digital *** topics of research and practice,including modifiable risk factors leading to a dramatic increase in Alzheimer’s disease and other forms of dementia,warrant deeper insight into the evidence-based knowledge available in the *** goal is to provide researchers with a visual-based easy traversal through a digital repository of research *** paper takes the first step in proposing a novel integrated model using knowledge maps and next-generation graph datastores to achieve a semantic visualization with domain-specific knowledge,such as dementia risk *** model facilitates a deep conceptual understanding of the literature by automatically establishing visual relationships among the extracted knowledge from the big data resources of research *** also serves as an automated tool for a visual navigation through the knowledge repository for faster identification of dementia risk factors reported in scholarly ***,it facilitates a semantic visualization and domain-specific knowledge discovery from a large digital repository and their associations.

关键词： Big data Data visualization Knowledge maps Dementia Non-relational database graph database Neo4j Semantic visualization

Construction and application of knowledge graph of Treatise on Febrile Diseases

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Digital Chinese Medicine 2022年第4期5卷 394-405页

作者： LIU Dongbo WEI Changfa XIA Shuaishuai YAN Junfeng School of Informatics Hunan University of Chinese MedicineChangshaHunan 410208China

Objective To establish the knowledge graph of“disease-syndrome-symptom-method-formula”in Treatise on Febrile Diseases(Shang Han Lun,《伤寒论》)for reducing the fuzziness and uncertainty of data,and for laying a foundation for later knowledge reasoning and its *** Under the guidance of experts in the classical formula of traditional Chinese medicine(TCM),the method of“top-down as the main,bottom-up as the auxiliary”was adopted to carry out knowledge extraction,knowledge fusion,and knowledge storage from the five aspects of the disease,syndrome,symptom,method,and formula for the original text of Treatise on Febrile Diseases,and so the knowledge graph of Treatise on Febrile Diseases was *** this basis,the knowledge structure query and the knowledge relevance query were realized in a visual *** The knowledge graph of“disease-syndrome-symptom-method-formula”in the Treatise on Febrile Diseases was constructed,containing 6469 entities and 10911 relational triples,on which the query of entities and their relationships can be carried out and the query result can be *** The knowledge graph of Treatise on Febrile Diseases systematically realizes its digitization of the knowledge system,and improves the completeness and accuracy of the knowledge representation,and the connection between“disease-syndrome-symptom-treatment-formula”,which is conducive to the sharing and reuse of knowledge can be obtained in a clear and efficient way.

关键词： Treatise on Febrile Diseases(Shang Han Lun,《伤寒论》) Knowledge graph Ontology graph database Knowledge extraction Knowledge fusion

The Performance Evaluation and Resilience Analysis of Supply Chain Based on Logistics Network

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The Performance Evaluation and Resilience Analysis of Supply...