Exploiting Information-Centric Networking to Federate Spatial Databases

Detti, Andrea; Rossi, Giulio; Melazzi, Nicola Blefari

doi:10.1109/access.2019.2953043

Cited by 4 publications

(4 citation statements)

References 24 publications

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“…En la aplicación del método cuantitativo se obtuvo un análisis de las diferentes características comparativas como la facilidad de uso, configuraciones, calidad de servicio, entre otros que sobresalen en las bases de datos NoSQL clave/valor. Las características que se analizaron en [11], posterior a ello, se evaluó y se puso a prueba por los autores de este artículo, los resultados obtenidos se muestran en la Tabla 2.…”

Section: Resultsunclassified

NoSQL Database Benchmarking: Key/value in an Application-building Environment

Miranda,

Oña,

Mendoza

et al. 2024

espoch

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The proportion of data generated is constantly growing as the number and variety of connected devices increase, advances in data storage and mining supporting this evolution bring along the development of new techniques for searching and accessing data and realizing applications. This article was developed to carry out a comparative analysis of three databases: Redis, CouchBase, and Amazon DynamoDB to provide key characteristics to choose the right keyvalue NoSQL system for the type of applications, data used, and data processing. This was done through qualitative and quantitative research by expressing the results through comparative tables with characteristics that were obtained through a literature review and defined by the authors after the use of each of the databases. It can be concluded from the study of quantitative data that DynamoBD is highly rated for its ease of use, easy configuration, automatic retrieval, and data replication. However, in the qualitative data, CouchBase is the best option for the user considering it is cross-platform and can be adapted to websites, apps, etc. Keywords: Redis, CouchBase, DynamonDB, Web Applications, NoSQL. Resumen La proporción de datos generados crece constantemente a medida que aumenta la cantidad y variedad de dispositivos conectados, los avances en el almacenamiento y la extracción de datos respaldan esta evolución, la cual trajo consigo el desarrollo de nuevas técnicas para buscar y acceder a los datos y realización de aplicaciones. Este artículo se desarrolló con el objetivo de realizar un análisis comparativo de tres bases de datos: Redis, CouchBase y Amazon DynamoDB. Con la finalidad de proporcionar características claves para elegir el sistema NoSQL clave-valor correcto para el tipo de aplicaciones, datos utilizados y procesamiento de datos. Se realizó mediante investigación de índole cualitativa y cuantitativa al expresar los resultados mediante cuadros comparativos con características que fueron obtenidas a través de una revisión bibliográfica y definidos por los autores posterior al uso de cada una de las bases de datos. Se puede concluir que con el estudio de los datos cuantitativos DynamoBD obtiene una alta calificación por su fácil uso, fácil configuración, recuperación automática y replicación de datos. No obstante, en los datos cualitativos CouchBase es la mejor opción para el usuario por ser de multiplataforma que se puede adaptar a sitios web, aplicaciones, etc. Palabras Clave: Redis, Couchbase, DynamoDB, Aplicaciones Web, NoSQL.

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Section: Resultsunclassified

NoSQL Database Benchmarking: Key/value in an Application-building Environment

Miranda,

Oña,

Mendoza

et al. 2024

espoch

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“…In related research on MongoDB, attention has focused on geospatial data management and storage [34][35][36][37][38][39][40][41][42][43] and on index development methods [29,[44][45][46]. Using MongoDB, several platforms and frameworks have been designed to solve diverse application demands.…”

Section: ] }mentioning

confidence: 99%

“…There was one article about the Couchbase database in the search results, which is mentioned in Section 3. In it, an information-centric network was adopted to federate MongoDB and Couchbase databases [35]. The functional architecture of the designed federated database included a federation front-end for effective connection between a query processor and users; the query processor for interacting with local and remote DBSes; and a DBMS adapter for translating the federated query into the local query language in a local DBMS [35].…”

Section: Couchbasementioning

confidence: 99%

State-of-the-Art Geospatial Information Processing in NoSQL Databases

Guo

Onstein

2020

IJGI

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Geospatial information has been indispensable for many application fields, including traffic planning, urban planning, and energy management. Geospatial data are mainly stored in relational databases that have been developed over several decades, and most geographic information applications are desktop applications. With the arrival of big data, geospatial information applications are also being modified into, e.g., mobile platforms and Geospatial Web Services, which require changeable data schemas, faster query response times, and more flexible scalability than traditional spatial relational databases currently have. To respond to these new requirements, NoSQL (Not only SQL) databases are now being adopted for geospatial data storage, management, and queries. This paper reviews state-of-the-art geospatial data processing in the 10 most popular NoSQL databases. We summarize the supported geometry objects, main geometry functions, spatial indexes, query languages, and data formats of these 10 NoSQL databases. Moreover, the pros and cons of these NoSQL databases are analyzed in terms of geospatial data processing. A literature review and analysis showed that current document databases may be more suitable for massive geospatial data processing than are other NoSQL databases due to their comprehensive support for geometry objects and data formats and their performance, geospatial functions, index methods, and academic development. However, depending on the application scenarios, graph databases, key-value, and wide column databases have their own advantages.

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“…This document presented an architecture for federating spatial databases, such as the formation and grouping of common data; through a framework for a secure data center made up of layers [33].…”

Section: A Materialsmentioning

confidence: 99%

Analysis for the Evaluation and Security Management of a Database in a Public Organization to Mitigate Cyber Attacks

et al. 2020

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In data handling, security and privacy are essential for database administrators and users that own their information. Information about security models or architectures was analyzed for databases that minimize Cyber Attacks. The problem is that security models deployed in databases in public organizations suffer from computer attacks due to vulnerabilities in their security management systems. Data providers often publish the information for research purposes, publishing compromises on the privacy of the data of users registered in the entities. There are many security techniques for databases based on data encryption processes in transactions, however, the techniques found compromise information. The development of the document used the deductive method and exploratory research technique that allows us to study the information in the articles presented. In this document we have proposed a Security Model Assessment Prototype for Databases, a Prototype of Security Management Architecture in Blockchain for a Database, a Database Security Algorithm, a Logical Structure of the Management System in Blockchain, and a Prototype to mitigate cyberattacks. The use of a hybrid blockchain model provides the system with the optimal security that public organizations in relation to test results performed with a 99.50% security effectiveness. The simulations presented in this document were conducted based on in-depth studies and the data were randomly placed with a range according to the study results based on real-world situations.INDEX TERMS Blockchain, cyber attacks, cyber security, data base, public organization.

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Exploiting Information-Centric Networking to Federate Spatial Databases

Cited by 4 publications

References 24 publications

NoSQL Database Benchmarking: Key/value in an Application-building Environment

NoSQL Database Benchmarking: Key/value in an Application-building Environment

State-of-the-Art Geospatial Information Processing in NoSQL Databases

Analysis for the Evaluation and Security Management of a Database in a Public Organization to Mitigate Cyber Attacks

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