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A transaction platform for microservices-based big data systems

SIMULATION MODELLING PRACTICE AND THEORY 2023年 123卷

作者： Gonzalez-Aparicio, Maria Teresa Younas, Muhammad Tuya, Javier Casado, Ruben Univ Oviedo Polytech Sch Engn Gijon 33204 Spain Oxford Brookes Univ Sch Engn Comp & Math Oxford OX33 1HX Oxon England Accenture SL Sci & Technol Pk Gijon 33203 Spain

Microservices architecture has increasingly been adopted for building distributed and scalable applications. The premise is that microservices are designed as smaller software components which are easier to be preserved and which enable separation between different components. This paper proposes a new transaction platform for microservices architecture to manage processing of big data stored in a cluster of nosql databases. New asynchronous protocols are designed to execute database operations as transactions, and to maintain their correctness and consistency. A prototype system has been developed that simulates London bus service across bus routes. It is evaluated through simulation experiments using big data from 'Transport for London' data ser-vice in order to analyse effects of transaction processing on response time and throughput in microservices architecture. The transaction platform reliably processes database operations, and enables data availability and consistency in failure-free and failure-prone environments.

关键词： Microservices architecture Transaction management Big data nosql database

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FIMED: Flexible management of biomedical data

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COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2021年 212卷 106496-106496页

作者： Hurtado, Sandro Garcia-Nieto, Jose Navas-Delgado, Ismael Aldana-Montes, Jose F. Univ Malaga ITIS Software Khaos Res Arquitecto Francisco Penalosa 18 Malaga 29071 Spain Univ Malaga Biomed Res Inst Malaga IBIMA Malaga Spain Univ Malaga Dept Lenguajes & Ciencias Computac Malaga Spain

Background and objectives: In the last decade, clinical trial management systems have become an essential support tool for data management and analysis in clinical research. However, these clinical tools have design limitations, since they are currently not able to cover the needs of adaptation to the continuous changes in the practice of the trials due to the heterogeneous and dynamic nature of the clinical research data. These systems are usually proprietary solutions provided by vendors for specific tasks. In this work, we propose FIMED, a software solution for the flexible management of clinical data from multiple trials, moving towards personalized medicine, which can contribute positively by improving clinical researchers quality and ease in clinical trials. Methods: This tool allows a dynamic and incremental design of patients' profiles in the context of clinical trials, providing a flexible user interface that hides the complexity of using databases. Clinical researchers will be able to define personalized data schemas according to their needs and clinical study specifications. Thus, FIMED allows the incorporation of separate clinical data analysis from multiple trials. Results: The efficiency of the software has been demonstrated by a real-world use case for a clini-cal assay in Melanoma disease, which has been indeed anonymized to provide a user demonstration. FIMED currently provides three data analysis and visualization components, guaranteeing a clinical ex-ploration for gene expression data: heatmap visualization, clusterheatmap visualization, as well as gene regulatory network inference and visualization. An instance of this tool is freely available on the web at https://***/fimed . It can be accessed with a demo user account, "researcher", using the password "demo". Conclusion: This paper shows FIMED as a flexible and user-friendly way of managing multidimensional clinical research data. Hence, without loss of generality, FIMED is flexible e

关键词： Clinical trial management systems Clinical research nosql database MongoDB Gene expression data analysis Melanoma disease

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Applying nosql Data Adapter with the Learning Paths mechanism for better knowledge transfer in the age of distance learning

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Procedia Computer Science 2022年 207卷 3330-3339页

作者： Aleksandra Werner Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Akademicka 16 Str. 44-100 Gliwice Poland

database technology applies to many engineering problems. Hence it is the subject of study at many university majors. Since teaching practical usage of theory at a distance is difficult or even impossible, we present novel mechanisms that significantly enrich e-learning platform functionalities in individualized learning of databases installed on the teacher-managed server. The crucial component of our proposal, Data Adapter, allows for interactive querying and manipulating of the nosql databases through an e-learning platform. The Adapter is complemented by the Learning Paths component, which enables teachers the creation of individualized didactic paths for students with special educational needs. The e-learning platform load tests confirm that new activities do not substantially affect the comfort of students’ work. Its impact on learning effectiveness was verified by rating the competence test for the group of 104 course participants. Half of them were the participants of the e-learning nosql course and used the developed mechanisms, while the remaining, control, group was taught with the conventional methods. The research shows that the proposal successfully improves teaching modern nosql languages. The scores improvement in the e-learning group of students compared to results in the control group is noticeable, and observed differences are statistically significant.

关键词： e-learning interactive querying ’Learn-as-you-go’ paradigm learning effectiveness Learning Paths nosql database

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Graph-based data management system for efficient information storage, retrieval and processing

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INFORMATION PROCESSING & MANAGEMENT 2023年第2期60卷

作者： Aldwairi, Monther Jarrah, Moath Mahasneh, Naseem Al-khateeb, Baghdad Jordan Univ Sci & Technol Comp & Informat Technol POB 3030 Irbid 22110 Jordan Zayed Univ Coll Technol Innovat POB 144534 Abu Dhabi U Arab Emirates

Data management systems rely on a correct design of data representation and software components. The data representation scheme plays a vital role in how the data are stored, which influences the efficiency of its processing and retrieval. The system components design realizes software engineering concepts to enable performance metrics such as scalability, efficiency, flexibility, maintainability, and extendibility. This paper presents a data management system that uses a graph-based data representation scheme to achieve an efficient data retrieval when using graph-based databases. Input data are transformed into vertices, edges, and labels while inserting them into the database. The proposed system consists of three layers which are: system beans layer, data access layer, and the database engine. Healthcare data are used to evaluate the system in comparison with resource description framework (RDF) semantics. Extensive experiments are conducted to compare different scenarios of data storage and retrieval using Neo4J, OrientDB, and RDF4J. Experimental results show that the performance of the proposed graph-based approach outperforms RDF4J framework in terms of insertion and retrieval time.

关键词： Graph -based modeling nosql database RDF semantics Healthcare databases

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XML data manipulation in conventional and temporal XML databases: A survey

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COMPUTER SCIENCE REVIEW 2020年 36卷 100231-100231页

作者： Brahmia, Zouhaier Hamrouni, Hind Bouaziz, Rafik Univ Sfax Fac Econ & Management Dept Comp Sci Sfax Tunisia

After more than two decades of its use, XML is not only a standard format for exchanging data between different (Web) applications but also a model for a family of some emerging or nosql databases, called XML databases. In addition to its efficiency in the management of conventional data (i.e., data without a temporal reference), XML is also an excellent support for storing, manipulating, and querying temporal data, due its hierarchical structure. Besides, although several survey papers have dealt with multiple aspects concerning XML data, like XML data modeling, storage, indexing, and querying, there is no survey on the XML data manipulation (i.e., XML data insertion, deletion and modification) topic that continues interesting researchers of the database community, both in conventional and temporal XML databases. For that reason, we think that it is interesting to have a paper that reviews and compares research contributions dealing with this topic. So, our present paper (i) provides an overview of the state-of-the-art of XML data manipulation, in conventional and temporal XML databases, (ii) studies the support of such functionality in mainstream commercial DBMSs and (iii) gives some remarks on possible future research directions related to this issue. (c) 2020 Elsevier Inc. All rights reserved.

关键词： XML XML database nosql database Temporal XML database XML data manipulation Data manipulation operation

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Enhancing Digital Health Services with Big Data Analytics

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BIG DATA AND COGNITIVE COMPUTING 2023年第2期7卷 64页

作者： Berros, Nisrine El Mendili, Fatna Filaly, Youness El Idrissi, Younes El Bouzekri Ibn Tofail Univ Natl Sch Appl Sci Engn Sci Lab Kenitra 14000 Morocco Moulay Ismail Univ Sch Technol Image Lab Meknes 50050 Morocco

Medicine is constantly generating new imaging data, including data from basic research, clinical research, and epidemiology, from health administration and insurance organizations, public health services, and non-conventional data sources such as social media, Internet applications, etc. Healthcare professionals have gained from the integration of big data in many ways, including new tools for decision support, improved clinical research methodologies, treatment efficacy, and personalized care. Finally, there are significant advantages in saving resources and reallocating them to increase productivity and rationalization. In this paper, we will explore how big data can be applied to the field of digital health. We will explain the features of health data, its particularities, and the tools available to use it. In addition, a particular focus is placed on the latest research work that addresses big data analysis in the health domain, as well as the technical and organizational challenges that have been discussed. Finally, we propose a general strategy for medical organizations looking to adopt or leverage big data analytics. Through this study, healthcare organizations and institutions considering the use of big data analytics technology, as well as those already using it, can gain a thorough and comprehensive understanding of the potential use, effective targeting, and expected impact.

关键词： big health data electronic health records analytics machine learning nosql database

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A Semantic nosql Application Program Interface for Big Data

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INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS 2022年第12期13卷 715-726页

作者： ElDahshan, K. Elsayed, E. K. Mancy, H. AbuBakr, A. Al Azhar Univ Fac Sci Dept Math Cairo Egypt Al Azhar Univ Fac Sci Girls Dept Math Cairo Egypt Canadian Int Coll Comp Sci Inst Cairo Egypt

Complexity heterogeneity, schemaless-ness, data visualization, and extraction of consistent knowledge from Big Data are the biggest challenges in nosql databases. This paper presents a general semantic nosql Application Program Interface that integrates and converts nosql databases to semantic representation. The generated knowledge base is suitable for visualization and knowledge extraction from different Big Data sources. The authors use a case study of the COVID-19 pandemic prediction and other weather occurrences in various parts of the world to illustrate the suggested API. The Authors find a correlation between COVID-19 spread and deteriorating weather. According to the experimental findings, the API's performance is enough for heterogeneous Big Data.

关键词： nosql database formatting semantic technology data integration pandemic prediction

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Research on performance testing model of databases of different structure

Research on performance testing model of databases of differ...

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2019 2nd International Conference on Mechanical,Electronic and Engineering Technology(MEET 2019)

作者： Liu Xiaochuang Institute of Network Technology Beijing University of Posts and Telecommunications

Using our self-innovate performance testing software PTF, Performance Testing Facility, this paper comes up with a new performance testing model and executes performance testing on many databases of different structure. The databases of different structure include HBase, MySQL, Oracle, DM7 and etc. After analyzing different features of these databases according to the result, we get the same standard as in the industry, which proves the usability of our model.

关键词： performance testing relational database nosql database HBase

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Hadoop-HBase for Large-Scale Data

Hadoop-HBase for Large-Scale Data

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2011 International Conference on Computer Science and Network Technology(2011计算机科学与网络技术国际会议 ICCSNT 2011)

作者： Mehul Nalin Vora Innovation Labs PERC Tata Consultancy Services (TCS) Ltd. Mumbai India

Today we are inundated with digital data. Yet we are very poor in managing and processing it It is becoming increasingly difficult to store and analyze data efficiently and economically via conventional database management tools. Not only that, type of data, appearing in the databases, are also changing. Now a day, binary large objects are a standard integral part of any database. Researchers, all over the globe, are baffling with analysis of these ultra large databases. Apache HBase is one such attempt HBase is a nosql distributed database developed on top of Hadoop Distributed File System (HDFS). In this paper, we present an evaluation of hybrid architecture where HDFS contains the non-textual data like images and location of such data is stored in HBase. This hybrid architecture enables faster search and retrieval of the data which is a growing need in any organization who are flooded with data. The paper aims at evaluating the performance of random reads and random writes of data storage location information to HBase and retrieving and storing data in HDFS respectively. We also present a comparative study of HBase-HDFS architecture with MySQL-HDFS architecture.

关键词： large-scale data distributed storage Hadoop HDFS Map Reduce HBase nosql database

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SD: A Divergence-Based Estimation Method for Service Demands in Cloud Systems

SD: A Divergence-Based Estimation Method for Service Demands...

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International Conference on Future Internet of Things and Cloud (FiCloud)

作者： Salvatore Dipietro Giuliano Casale Department of Computing Imperial College London United Kingdom

ISBN: (纸本)9781728128894

Estimating performance models parameters of cloud systems presents several challenges due to the distributed nature of the applications, the chains of interactions of requests with architectural nodes, and the parallelism and coordination mechanisms implemented within these systems. In this work, we present a new inference algorithm for model parameters, called state divergence (SD) algorithm, to accurately estimate resource demands in a complex cloud application. Differently from existing approaches, SD attempts to minimize the divergence between observed and modeled marginal state probabilities for individual nodes within an application, therefore requiring the availability of probabilistic measures from both the system and the underpinning model. Validation against a case study using the Apache Cassandra nosql database and random experiments show that SD can accurately predict demands and improve system behavior modeling and prediction.

关键词： Service demands inference queueing cloud nosql database Clouds Queue Inference algorithms Model checking Statistical analysis parallelism Legal Services

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