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Managing Data in Healthcare Information Systems: Many Models, One Solution

COMPUTER 2015年第3期48卷 52-59页

作者： Kaur, Karamjit Rani, Rinkle Thapar Univ Dept Comp Sci & Engn Patiala 147004 Punjab India

Because healthcare data comes from multiple, vastly different sources, databases must adopt a range of models to process and store it. A polyglot-persistent framework combines relational, graph, and document data mode... 详细信息

关键词： SQL data models document handling electronic health records health care relational databases nosql data stores data management data processing data storage document data model graph data model healthcare data healthcare information systems polyglot-persistent framework relational data model relational data store Big data Data models Database languages Knowledge based systems Medical information processing Medical services Relational databases MongoDB Neo4j nosql databases big data data management healthcare data management

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Knowledge discovery from social media using big data-provided sentiment analysis (SoMABiT)

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JOURNAL OF INFORMATION SCIENCE 2015年第6期41卷 779-798页

作者： Bohlouli, Mahdi Dalter, Jens Dornhoefer, Mareike Zenkert, Johannes Fathi, Madjid Univ Siegen D-57076 Siegen Germany

In today's competitive business world, being aware of customer needs and market-oriented production is a key success factor for industries. To this aim, the use of efficient analytical algorithms ensures better understanding of customer feedback and improves the next generation of products. Accordingly, the dramatic increase in the use of social media in daily life provides beneficial sources for market analytics. Yet how traditional analytic algorithms and methods can be scaled up for such disparate and multistructured data sources is a major challenge. This paper presents and discusses the technological and scientific focus of SoMABiT as a social media analysis platform using big data technology. Sentiment analysis has been employed in order to discover knowledge from social media. The use of MapReduce and the development of a distributed algorithm towards an integrated platform that can scale for any data volume and provide social media-driven knowledge is the main novelty of the proposed concept in comparison to the state-of-the-art technologies.

关键词： Big data analytics knowledge discovery nosql databases product use information semantic technologies sentiment analysis social media analysis

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Performance and Scalability of Voldemort nosql 10

Performance and Scalability of Voldemort NoSQL

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10th Iberian Conference on Information Systems and Technologies (CISTI)

作者： Neves, Ricardo Bernardino, Jorge Inst Politecn Coimbra ISEC Coimbra Portugal Univ Coimbra ISEC Inst Politecn Coimbra CISUC Ctr Informat & Sistemas Coimbra Portugal

ISBN: (纸本)9781479983308

Currently companies need database engines able to process and store massive quantity of data. Traditional databases due to the large amount of unstructured data have trouble processing this amount of data in an acceptable time for businesses. To solve these problems recently emerged the nosql databases, offering great performance, flexibility and scalability. In this paper we evaluate the performance and scalability of a popular nosql database, Voldemort, using Yahoo! Cloud Serving Benchmark.

关键词： nosql databases performance scalability

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Data De duplication Using N0SQL databases in Cloud

Data De duplication Using N0SQL Databases in Cloud

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International Conference on Soft-Computing and Network Security (ICSNS)

作者： Backialakshmi, N. Manikandan, M. Adhiyamaan Coll Engn Comp Sci & Engn Hosur Tamil Nadu India Adhiyamaan Coll Engn Dept CSE Hosur Tamil Nadu India

ISBN: (纸本)9781479917532

Data de-duplication has an important role in reducing storage consumption to make it affordable to manage in today's explosive data growth. Numerous DD methodologies like chunking and, delta encoding are available to optimize the use of storage. These technologies approach DD at file and/or sub-file level but this approach has never been optimal for nosql DBs. This method proposes data De-Duplication in nosql databases (DDNSDB) which makes use of a DD approach at a higher level of abstraction. The main goals of this research is, to maximally reduce the amount of duplicates in one type of nosql DBs, namely the key-value store, to maximally increase the process performance such that the backup window is marginally affected, and to design with horizontal scaling in mind such that it would run on a Cloud Platform competitively. Also, by following an optimized adapted Map Reduce architecture, DDNSDB proves to have competitive performance advantage in a horizontal scaling cloud environment compared with a vertical scaling environment.

关键词： Data De duplication nosql databases Map reduce

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Cascket: A Binary Protocol based C Client-Driver for Apache Cassandra

Cascket: A Binary Protocol based C Client-Driver for Apache ...

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International Conference on Advances in Computing, Communications and Informatics ICACCI

作者： Karpate, Sarang Joshi, Abhishek Dosani, Javed Abraham, Jibi Coll Engn Pune COEP Dept Comp Engn & Informat Technol Pune Maharashtra India

ISBN: (纸本)9781479987924

Few can deny the diverse applications of nosql Database technology today. The last decade has witnessed an exponential rise in not only data generation but also in the manipulation and management of the same. nosql Technologies have engendered a new platform for large enterprises to come up and have provided them a wide vista for data manipulation. Moreover, existing technologies have been augmented with the unique features that this technology offers. Apache Cassandra is one of the leading nosql databases today. The rise of Cassandra has also given rise to corresponding high level client drivers. There are several drivers present today for interfacing Cassandra with languages such as PHP, Java, C++, etc. However, to the best of our knowledge, no such driver for C exists. This paper proposes such a driver, 'Cascket' that allows direct communication of Cassandra over C without the existence of a middle-ware.

关键词： Cassandra Cassandra Binary Protocol C Client-driver nosql databases systems

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Dependable Horizontal Scaling Based On Probabilistic Model Checking 15

Dependable Horizontal Scaling Based On Probabilistic Model C...

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2015 15th IEEE ACM International Symposium on Cluster Cloud and Grid Computing (CCGrid 2015)

作者： Naskos, Athanasios Stachtiari, Emmanouela Gounaris, Anastasios Katsaros, Panagiotis Tsoumakos, Dimitrios Konstantinou, Ioannis Sioutas, Spyros Aristotle Univ Thessaloniki Thessaloniki Greece Natl Tech Univ Athens Athens Greece Ionian Univ Corfu Greece

ISBN: (纸本)9781479980062

The focus of this work is the on-demand resource provisioning in cloud computing, which is commonly referred to as cloud elasticity. Although a lot of effort has been invested in developing systems and mechanisms that enable elasticity, the elasticity decision policies tend to be designed without quantifying or guaranteeing the quality of their operation. We present an approach towards the development of more formalized and dependable elasticity policies. We make two distinct contributions. First, we propose an extensible approach to enforcing elasticity through the dynamic instantiation and online quantitative verification of Markov Decision Processes (MDP) using probabilistic model checking. Second, various concrete elasticity models and elasticity policies are studied. We evaluate the decision policies using traces from a real nosql database cluster under constantly evolving external load. We reason about the behaviour of different modeling and elasticity policy options and we show that our proposal can improve upon the state-of-the-art in significantly decreasing under-provisioning while avoiding over-provisioning.

关键词： nosql databases PRISM autonomic computing cloud elasticity quantitative verification

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Antares: A Scalable, Real-time, Fault tolerant Data Store for Spatial Analysis

Antares: A Scalable, Real-time, Fault tolerant Data Store fo...

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IEEE 11th World Congress on Services

作者： Simmonds, Rebecca Watson, Paul Halliday, Jonathan Newcastle Univ Sch Comp Sci Newcastle Upon Tyne NE1 7RU Tyne & Wear England Red Hat Newcastle Upon Tyne Tyne & Wear England

ISBN: (纸本)9781467372756

The growth of mobile devices has significantly increased the velocity and volume of location-based data. Whilst there is enormous potential for applications that exploit this data in real-time, storing and querying it in real-time creates significant challenges. Traditional RDBMS systems are not sufficiently scalable, while typical cloud-based solutions such as map-reduce do not possess the capabilities required for real-time, spatial-data processing. Therefore, new approaches are needed. In this paper we explore the use of nosql technologies. These offer scalability, availability and fault tolerance, but - as we show - do not perform well with spatial data. Therefore, in this paper we address this challenge by enhancing existing spatial indexing structures with novel algorithms for inserting and searching spatial data. We have implemented this in a nosql solution (Antares), and evaluated it against two other nosql solutions, and a range of indexing structures: Kd-Tree, Quad Tree and Geohashing. The results show that Antares significantly outperforms the other approaches.

关键词： nosql databases multidimensional analysis geospatial analysis real-time and scalability

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nosql Data Model for Semi-automatic Integration of Ethnomedicinal Plant Data from Multiple Sources

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PHYTOCHEMICAL ANALYSIS 2014年第6期25卷 495-507页

作者： Ningthoujam, Sanjoy Singh Choudhury, Manabendra Dutta Potsangbam, Kumar Singh Chetia, Pankaj Nahar, Lutfun Sarker, Satyajit D. Basar, Norazah Talukdar, Anupam Das Ghanapriya Womens Coll Dept Bot Imphal Manipur India Assam Univ Bioinformat Ctr Silchar Assam India Manipur Univ Dept Life Sci Imphal Manipur India Liverpool John Moores Univ Sch Pharm & Biomol Sci Med Chem & Nat Prod Res Grp Fac Sci Liverpool L3 3AF Merseyside England UTM Dept Chem Fac Sci Skudai 81310 Johor Malaysia Assam Univ Dept Life Sci & Bioinformat Silchar Assam India

IntroductionSharing traditional knowledge with the scientific community could refine scientific approaches to phytochemical investigation and conservation of ethnomedicinal plants. As such, integration of traditional knowledge with scientific data using a single platform for sharing is greatly needed. However, ethnomedicinal data are available in heterogeneous formats, which depend on cultural aspects, survey methodology and focus of the study. Phytochemical and bioassay data are also available from many open sources in various standards and customised formats. ObjectiveTo design a flexible data model that could integrate both primary and curated ethnomedicinal plant data from multiple sources. Materials and methodsThe current model is based on MongoDB, one of the Not only Structured Query Language (nosql) databases. Although it does not contain schema, modifications were made so that the model could incorporate both standard and customised ethnomedicinal plant data format from different sources. ResultsThe model presented can integrate both primary and secondary data related to ethnomedicinal plants. Accommodation of disparate data was accomplished by a feature of this database that supported a different set of fields for each document. It also allowed storage of similar data having different properties. ConclusionThe model presented is scalable to a highly complex level with continuing maturation of the database, and is applicable for storing, retrieving and sharing ethnomedicinal plant data. It can also serve as a flexible alternative to a relational and normalised database. Copyright (c) 2014 John Wiley & Sons, Ltd. Scientific approaches to phytochemical investigation and conservation of ethnomedicinal plants could be refined by sharing traditional knowledge with scientific community, by integrating traditional knowledge with scientific data in a single platform. To address this issue, a platform based on MongoDB, one of the nosql databases, has been proposed. T

关键词： MongoDB nosql databases ethnomedicinal plants

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Performance Characterization of Hyperscale Applicationson on NVMe SSDs 15

Performance Characterization of Hyperscale Applicationson on...

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Proceedings of the 2015 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems

作者： Qiumin Xu Huzefa Siyamwala Mrinmoy Ghosh Manu Awasthi Tameesh Suri Zvika Guz Anahita Shayesteh Vijay Balakrishnan University of Southern California Los Angeles CA USA San Jose State University San Jose CA USA Samsung Semiconductor Inc Milpitas CA USA

ISBN: (纸本)9781450334860

The storage subsystem has undergone tremendous innovation in order to keep up with the ever-increasing demand for throughput. NVMe based SSDs are the latest development in this domain, delivering unprecedented performance in terms of both latency and peak bandwidth. Given their superior performance, NVMe drives are expected to be particularly beneficial for I/O intensive applications in datacenter installations. In this paper we identify and analyze the different factors leading to the better performance of NVMe SSDs. Then, using databases as the prominent use-case, we show how these would translate into real-world benefits. We evaluate both a relational database (MySQL) and a nosql database (Cassandra) and demonstrate significant performance gains over best-in-class enterprise SATA SSDs: from 3.5x for TPC-C and up to 8.5x for Cassandra.

关键词： hyperscale applications nvme ssds nosql databases performance characterization

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The Distributed Storage Strategy Research of Remote Sensing Image Based on Mongo DB 3

The Distributed Storage Strategy Research of Remote Sensing ...

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3rd International Workshop on Earth Observation and Remote Sensing Applications (EORSA)

作者： Li Chaokui Yang Wu Hunan Univ Sci & Technol Natl Local Joint Engn Lab Geospatial Informat Tec Xiangtan Peoples R China

ISBN: (纸本)9781479941841

In recent years, with the wisdom of the city promote and research in the field of geographic space unceasingly thoroughly, the mass spatial data storage management and multiple concurrent access has become the research hotspot in the field of geosciences. Traditional spatial data storage is based on relational database, modeling, index mechanism, cache management and task scheduling method to realize the spatial data storage and scheduling. As a result of the limitation of performance, relational database already cannot satisfy the user's high concurrency read/write performance and large scale spatial data organization and management. In this article, through debris type partition algorithm for the image division, put forward the non-relational database of remote sensing image data storage strategy based on the Mongo DB, on the premise of high concurrent access, without significant decline of read/write speed. Through experiment contrast the storage efficiency and multiple concurrent access efficiency with the remote sensing image storage method based on SQL Server database, the results show that the multiple concurrent access efficiency of the remote sensing image data storage based on Mongo DB is much better than the latter.

关键词： Mongo DB nosql databases Debris typepartition algorithm SQL Server RS image

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