P
Pablo Basanta-Val
Researcher at Charles III University of Madrid
Publications - 66
Citations - 1395
Pablo Basanta-Val is an academic researcher from Charles III University of Madrid. The author has contributed to research in topics: Real time Java & Java. The author has an hindex of 20, co-authored 66 publications receiving 1249 citations. Previous affiliations of Pablo Basanta-Val include Carlos III Health Institute & Complutense University of Madrid.
Papers
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Journal ArticleDOI
Next-Generation Big Data Analytics: State of the Art, Challenges, and Future Research Topics
TL;DR: Recent research in data types, storage models, privacy, data security, analysis methods, and applications related to network big data are reviewed.
Proceedings Article
Proportional Justified Representation
Luis Sánchez Fernández,Edith Elkind,Martin Lackner,Norberto Fernández García,Jesús Arias Fisteus,Pablo Basanta-Val,Piotr Skowron +6 more
TL;DR: In this article, a relaxation of justified representation, called Proportional Justified Representation (PJR), is proposed, which is more demanding than justified representation but compatible with perfect representation.
Journal ArticleDOI
QoS-Aware Real-Time Composition Algorithms for Service-Based Applications
TL;DR: Two algorithms are proposed for the composition of QoS-aware service-based applications with temporal requirements: an exhaustive algorithm that computes the optimal service combination in terms of a figure of merit, suitable for offline composition; and an improved algorithm based on heuristics and partial figures of merit suitable for online composition.
Journal ArticleDOI
Architecting Time-Critical Big-Data Systems
TL;DR: This paper deals with the definition of a time-critical big- data system from the point of view of requirements, analyzing the specific characteristics of some popular big-data applications and proposing an architecture and offering initial performance patterns that connect application costs with infrastructure performance.
Journal ArticleDOI
Improving the predictability of distributed stream processors
TL;DR: This article provides a set of improvements to a computational model called distributed stream processing in order to formalize it as a real-time infrastructure and proposes some extensions to Storm, one of the most popular stream processors.