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El autor Antonio Corral ha publicado 3 artículo(s):

1 - Creating datasets for data analysis through a cloud microservice-based architecture

Data analysis is a trending technique due to the tendency of analyzing patterns or generating knowledge in different domains. However, it is difficult to know at design time what raw data should be collected, how it is going to be analyzed or which analysis techniques will be applied to data. Service-oriented architectures can be applied to solve these problems by providing flexible and reliable architectures. In this paper, we present a microservice-based software architecture in the cloud with the aim of generating datasets to carry out data analysis. This architecture facilitates acquiring data, which may be located in a data center, distributed, or even on different devices (ubiquitous computing) due to the rise of the IoT. It provides an infrastructure over which multiple developer’ groups can work in parallel on the microservices. These microservices also provide a reliable and affordable adaptability to the lack of specific requirements in some functionalities and the fast evolution and variability of them, due to the fast changing of client needs.

Autores: Antonio Jesús Fernández-García / Javier Criado / Antonio Corral / Luis Iribarne / 
Palabras Clave: architectures - datasets - microservices

2 - A First Approach towards Storage and Query Processing of Big Spatial Networks in Scalable and Distributed Systems

Due to the ubiquitous use of spatial data applications and the large amounts of spatial data that these applications generate, the processing of large-scale queries in distributed systems is becoming increasingly popular. Complex spatial systems are very often organized under the form of Spatial Networks, a type of graph where nodes and edges are embedded in space. Examples of these spatial networks are transportation and mobility networks, mobile phone networks, social and contact networks, etc. When these spatial networks are big enough that exceed the capacity of commonly-used spatial computing technologies, we have Big Spatial Networks, and to manage them is necessary the use of distributed graph-parallel systems. In this paper, we describe our emerging work concerning the design of new storage methods and query processing algorithms over big spatial networks in scalable and distributed systems, which is a very active research area in the past years.

Autores: Manel Mena / Antonio Corral / Luis Iribarne / 
Palabras Clave: Distributed Systems - query processing - Spatial Networks - Storage Methods

3 - Efficient query processing on large spatial databases: A performance study

Processing of spatial queries has been studied extensively in the literature. In most cases, it is accomplished by indexing spatial data using spatial access methods. Spatial indexes, such as those based on the Quadtree, are important in spatial databases for efficient execution of queries involving spatial constraints and objects. In this paper, we study a recent balanced disk-based index structure for point data, called xBR+-tree, that belongs to the Quadtree family and hierarchically decomposes space in a regular manner. For the most common spatial queries, like Point Location, Window, Distance Range, Nearest Neighbor and Distance-based Join, the R-tree family is a very popular choice of spatial index, due to its excellent query performance. For this reason, we compare the performance of the xBR+-tree with respect to the R?-tree and the R+-tree for tree building and processing the most studied spatial queries. To perform this comparison, we utilize existing algorithms and present new ones. We demonstrate through extensive experimental performance results (I/O efficiency and execution time), based on medium and large real and synthetic datasets, that the xBR+-tree is a big winner in execution time in all cases and a winner in I/O in most cases.

Autores: George Roumelis / Michael Vassilakopoulos / Antonio Corral / Yannis Manolopoulos / 
Palabras Clave: Performance evaluation - Quadtrees - query processing - R-trees - Spatial access methods - Spatial databases - xBR-trees