2026-05-28T07:46:00Zhttps://riuma.uma.es/rest/oai/requestoai:riuma.uma.es:10630/250732026-02-03T10:50:02Zcom_10630_2254col_10630_37953
RIUMA. Repositorio Institucional de la Universidad de Málaga
author
Barquero Moreno, Gala
author
Troya-Castilla, Javier
author
Vallecillo-Moreno, Antonio Jesús
2022-09-26T05:37:15Z
2022-09-26T05:37:15Z
2020-11-20
https://hdl.handle.net/10630/25073
10.1007/s10270-020-00832-3
Querying large models efficiently often imposes high demands on system resources such as memory, processing time, disk access or network latency. The situation becomes more complicated when data are highly interconnected, e.g. in the form of graph structures, and when data sources are heterogeneous, partly coming from dynamic systems and partly stored in databases. These situations are now common in many existing social networking applications and geo-location systems, which require specialized and efficient query algorithms in order to make informed decisions on time. In this paper, we propose an algorithm to improve the memory consumption and time performance of this type of queries by reducing the amount of elements to be processed, focusing only on the information that is relevant to the query but without compromising the accuracy of its results. To this end, the reduced subset of data is selected depending on the type of query and its constituent f ilters. Three case studies are used to evaluate the performance of our proposal, obtaining significant speedups in all cases.
eng
Algoritmos computacionales
Improving query performance on dynamic graphs
journal article
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URL
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File
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SoSyM2021_QueryPerformance_PrePrint.pdf