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International Conference on Wearable Sensors and Robots (ICWSR)

作者： Zhou, Chuan-hong Yao, Kun Jiang, Zhen-yang Bai, Wu-xia Shanghai Univ Shanghai Key Lab Intelligent Mfg & Robot Sch Mechatron Engn & Automat Shanghai 200072 Peoples R China

ISBN: (纸本)9789811024047;9789811024030

Intelligent manufacturing is a new trend that is a deep integration of information and industrialization. As to the information, database is very important. For the past 20 years, relational databases have been widely used in a lot of fields because of their rich feature, such as query capabilities and transaction management and so on. However, they do not have the capacity of storing and processing a large number of data effectively, and at the same time, they are not very efficient to make transactions and join operations. In order to adapt to the new demand, some of new databases have been invented which are not in accordance with relational model. These databases are known as nosql. The underlying data and transaction model of the nosql are different from relational database. Some of organizations have shown much interest in nosql and adopted this new technology, which promote further research on the nosql. In this thesis, we research nosql database about their origin and characteristics. Then, we compare between one of the nosql database, MongoDB, to the standard relational database, SQL Server. We contrast their performance from different aspects. Results show that MongoDB performs better than the relational database.

关键词： nosql databases MongoDB SQL server

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Demonstration of OpenGeoBase: the ICN nosql spatio-temporal database 23

Demonstration of OpenGeoBase: the ICN NoSQL spatio-temporal ...

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23rd IEEE International Symposium on Local and Metropolitan Area Networks (LANMAN)

作者： Orru, Michele Paolillo, Riccardo Detti, Andrea Rossi, Giulio Melazzi, Nicola Blefari Univ Roma Tor Vergata CNIT Elect Engn Dept Rome Italy

ISBN: (纸本)9781538607282

This paper describes a demo of OpenGeoBase, a nosql spatio-temporal distributed database that exploits Information Centric Network technology. We show its basic operations and two applications based on it. The first one is an Intelligent Transport System application making possible to discover public transport information (GTFS files) all over the world. The second application concerns a citizen reporting application though which users can post and search for geo-tagged photos.

关键词： Servers Europe Geometry Distributed databases nosql databases Spatial databases

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Fault Tolerant Streaming of Live News using Multi-node Cassandra 10

Fault Tolerant Streaming of Live News using Multi-node Cassa...

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10th International Conference on Contemporary Computing (IC3)

作者： Dhingra, Shubham Sharma, Shreeya Kaur, Parmeet Dabas, Chetna Jaypee Inst Informat Technol Dept Comp Sci & Informat Technol Noida India

ISBN: (纸本)9781538630778

The paper presents an Android application for streaming live news data using Multi-node Cassandra as the underlying data store. This application is designed for the modern era's users who constantly wish to keep themselves abreast of the latest or trending news with the help of online media. The application provides access to abstracted day-to-day trending news in various categories, for instance national, technical, sports, science etc. in a single swipe. Our application uses Apache Cassandra, a distributed nosql database management system, as a data store for distribution of news related data across 4 nodes. Cassandra has been used due to its capability to manage and manipulate large amounts of data across various commodity servers along with features of high availability and fault tolerance. For testing the distribution and replication of data across the nodes, one or more nodes were failed in the experiments. The results show successful retrieval of data despite node failure.

关键词： Apache Cassandra nosql databases Multi-node Cassandra Setup Replication Node-failure

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CRESON: Callable and Replicated Shared Objects over nosql 37

CRESON: Callable and Replicated Shared Objects over NoSQL

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37th IEEE International Conference on Distributed Computing Systems (ICDCS)

作者： Sutra, Pierre Riviere, Etienne Cotes, Cristian Sanchez Artigas, Marc Garcia Lopez, Pedro Bernard, Emmanuel Burns, William Zamarreno, Galder Univ Paris Saclay CNRS Telecom SudParis Paris France Univ Neuchatel Neuchatel Switzerland Univ Rovira & Virgili Tarragona Spain Red Hat Raleigh NC USA

ISBN: (纸本)9781538617915

In a Cloud environment, the ability to share and persist objects simplifies the design of applications. Storing objects in a nosql database ensures their availability and provides scalability to applications. When Object-nosql Mapping is performed at the client side, objects that are accessed by several clients are repeatedly converted between their in-memory and serialized representations. This negatively impacts performance and increases replication costs. In this paper, we describe the design of CRESON, a system supporting callable objects over nosql, in which application objects are mapped and instantiated directly on the storage nodes. CRESON supports composition by reference and ensures strong consistency. Objects are replicated and maintained coherent using State Machine Replication. The implementation of CRESON leverages the support of a listenable key-value store (LKVS), a novel nosql storage abstraction that we introduce in this paper. We discuss the performance and complexity of CRESON with the example of the portage of a personal cloud storage service, initially developed using an object-relational mapping over a sharded PostgreSQL database. Our results show that CRESON offers a simpler programming experience both in terms of learning time and lines of code, while performing better on average and being more scalable.

关键词： Elasticity Cloud computing nosql databases Java Scalability Impedance

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Big Data Storage and Management: Challenges and Opportunities 12th

Big Data Storage and Management: Challenges and Opportunitie...

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12th IFIP WG 5.11 International Symposium on Environmental Software Systems (ISESS)

作者： Pokorny, Jaroslav MFF UK Malostranske Nam 25 Prague 11800 Czech Republic

ISBN: (纸本)9783319899350;9783319899343

The paper is focused on today's very popular theme - Big Data. We describe and discuss its characteristics by eleven V's (Volume, Velocity, Variety, Veracity, etc.) and Big Data quality. These characteristics represent both data and process challenges. Then we continue with problems of Big Data storage and management. Principles of nosql databases are explained including their categorization. We also shortly describe Hadoop and MapReduce technologies as well as their inefficiency for some interactive queries and applications within the domain of large-scale graph processing and streaming data. nosql databases and Hadoop M/R are designed to take advantage of cloud computing architectures and allow massive computations to be run inexpensively and efficiently. The term of Big Data 1.0 was introduced for these technologies. We continue with some new approaches called currently Big Data 2.0 processing systems. Particularly their four categories are introduced and discussed: General purpose Big Data Processing Systems, Big SQL Processing Systems, Big Graph Processing Systems, and Big Stream Processing Systems. Then, an attention is devoted to Big Analytics - the main application area for Big Data storage and processing. We argue that enterprises with complex, heterogeneous environments no longer want to adopt a BI access point just for one data source (Hadoop). More heterogeneous software platforms are needed. Even Hadoop has become a multipurpose engine for ad hoc analysis. Finally, we mention some problems with Big Data. We also remind that Big Data creates a new type of digital divide. Having access and knowledge of Big Data technologies gives companies and people a competitive edge in today's data driven world.

关键词： Big Data nosql databases MapReduce Hadoop Big Data 2.0 Big Analytics

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An MDE Approach to Generate Schemas for Object-document Mappers 5

An MDE Approach to Generate Schemas for Object-document Mapp...

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5th International Conference on Model-Driven Engineering and Software Development (MODELSWARD)

作者： Sevilla Ruiz, Diego Feliciano Morales, Severino Garcia-Molina, Jesus Univ Murcia Fac Comp Sci Campus Espinardo Murcia Spain

ISBN: (纸本)9789897582103

Most nosql systems are schemaless. This lack of schema offers a greater flexibility than relational systems. However, this comes at the cost of losing benefits such as the static checking that assure that stored data conforms to the database schema. Instead, developers must be in charge of this task that is time-consuming and error-prone. Object-nosql mappers are emerging to alleviate this task and facilitate the development of nosql applications. These mappers allow the definition of schemas, which are used to assure that data are correctly manipulated. In this article, we present an MDE approach that automatically generates schemas and other artefacts for mappers. As proof of concept, we have considered Mongoose, which is a widely used mapper for MongoDB, but the solution is mapper-independent. Firstly, the schemas are inferred from stored data by using an approach defined in a previous work. Then, nosql schema models are input to a two-step model transformation chain that generates schemas, validators and updating procedures, among other Mongoose artefacts. An intermediate metamodel has been defined to ease the implementation of the transformations. This work shows how MDE techniques can be applied in the emerging "nosql Data Engineering" field.

关键词： nosql databases nosql Data Engineering Code Generation MDE Solution Object-document Mappers

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A performance evaluation of in-memory databases

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JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES 2017年第4期29卷 520-525页

作者： Kabakus, Abdullah Talha Kara, Resul Abant Izzet Baysal Univ IT Ctr TR-14030 Bolu Turkey Duzce Univ Fac Engn Dept Comp Engn TR-81620 Duzce Turkey

The popularity of nosql databases has increased due to the need of (1) processing vast amount of data faster than the relational database management systems by taking the advantage of highly scalable architecture, (2) flexible (schema-free) data structure, and, (3) low latency and high performance. Despite that memory usage is not major criteria to evaluate performance of algorithms, since these databases serve the data from memory, their memory usages are also experimented alongside the time taken to complete each operation in the paper to reveal which one uses the memory most efficiently. Currently there exists over 225 nosql databases that provide different features and characteristics. So it is necessary to reveal which one provides better performance for different data operations. In this paper, we experiment the widely used in-memory databases to measure their performance in terms of (1) the time taken to complete operations, and (2) how efficiently they use memory during operations. As per the results reported in this paper, there is no database that provides the best performance for all data operations. It is also proved that even though a RDMS stores its data in memory, its overall performance is worse than nosql databases. (C) 2016 The Authors. Production and hosting by Elsevier B.V. on behalf of King Saud University.

关键词： nosql databases In-memory databases Database performance

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An open Tool Architecture for Security Testing of nosql-based applications 14

An open Tool Architecture for Security Testing of NoSQL-base...

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14th IEEE/ACS International Conference on Computer Systems and Applications (AICCSA)

作者： Algarni, Abdullah Alsolami, Fawaz Eassa, Fathy Alsubhi, Khalid Jambi, Kamal Khemakhem, Maher King Abdulaziz Univ Fac Comp & Informat Technol CS Dept Jeddah Saudi Arabia

ISBN: (纸本)9781538635810

Injection attacks remain yet one of the major challenges in non-relational data stores or nosql databases. Indeed, such databases are intended to store big data and are classified into four categories;Key-values Stores, Wide Column Stores, Document Stores, and Graph databases. The different vulnerabilities of these nosql databases have attracted many researchers to attempt solving or mitigating this problem. Unfortunately, extensive experiments have revealed that all proposed approaches and techniques are away from the expectations. This is due mainly to their focusing only either on some parts of the problem or on a specific nosql engine. In this paper, we propose an open tool architecture which can take into consideration any nosql engines belonging to the four data stores categories whatever the programming language used. The proposed tool architecture is able to detect first vulnerable statements in the static mode on the developer side. Second, it detects also automatically injection attacks during run-time on the server side thanks to the added instrumenting statements during the first control (static mode). The easy expansion and adaptation of the proposed tool to any nosql engine and/or any kind of attacks and/or programming languages makes it very attractive compared the existing ones. Indeed nowadays, we observe the emergence of new kinds of attacks once a new security approach or framework or technique is proposed.

关键词： nosql databases injection attacks security testing

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Big data storage technologies： a survey

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Frontiers of Information Technology & Electronic Engineering 2017年第8期18卷 1040-1070页

作者： Aisha SIDDIQA Ahmad KARIM Abdullah GANI Faculty of Computer Science and Information Technology University of Malaya Kuala Lumpur 50603 Malaysia Department of Information Technology Bahauddin Zakariya University Multan 60000 Pakistan

There is a great thrust in industry toward the development of more feasible and viable tools for storing fast-growing volume, velocity, and diversity of data, termed ＇big data＇. The structural shift of the storage mechanism from traditional data management systems to nosql technology is due to the intention of fulfilling big data storage requirements. However, the available big data storage technologies are inefficient to provide consistent, scalable, and available solutions for continuously growing heterogeneous data. Storage is the preliminary process of big data analytics for real-world applications such as scientific experiments, healthcare, social networks, and e-business. So far, Amazon, Google, and Apache are some of the industry standards in providing big data storage solutions, yet the literature does not report an in-depth survey of storage technologies available for big data, investigating the performance and magnitude gains of these technologies. The primary objective of this paper is to conduct a comprehensive investigation of state-of-the-art storage technologies available for big data. A well-defined taxonomy of big data storage technologies is presented to assist data analysts and researchers in understanding and selecting a storage mecha- nism that better fits their needs. To evaluate the performance of different storage architectures, we compare and analyze the ex- isling approaches using Brewer＇s CAP theorem. The significance and applications of storage technologies and support to other categories are discussed. Several future research challenges are highlighted with the intention to expedite the deployment of a reliable and scalable storage system.

关键词： Big data Big data storage nosql databases Distributed databases CAP theorem Scalability Consistency-partition resilience Availability-partition resilience

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Implementation of Multidimensional databases in Column-Oriented nosql Systems 19th

Implementation of Multidimensional Databases in Column-Orien...

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19th East-European Conference on Advances in databases and Information Systems (ADBIS)

作者： Chevalier, Max El Malki, Mohammed Kopliku, Arlind Teste, Olivier Tournier, Ronan Univ Toulouse IRIT UMR 5505 F-31062 Toulouse France

ISBN: (纸本)9783319231358;9783319231341

nosql (Not Only SQL) systems are becoming popular due to known advantages such as horizontal scalability and elasticity. In this paper, we study the implementation of multidimensional data warehouses based on column-oriented nosql systems. To do this, we define a set of mapping rules that transform a conceptual multidimensional data model into a logical column-oriented model. We consider three ways (three sub-models) to structure conceptual multidimensional data model into a column-oriented model. Then, we show an implementation of the proposed rules. Finally, we focus, through experiment, on data loading, model-to-model conversion and OLAP cuboid computation.

关键词： Data warehouse design Multidimensional modelling nosql databases Model transformation rules Column-Oriented nosql model

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