M
Mario A. R. Dantas
Researcher at Universidade Federal de Juiz de Fora
Publications - 228
Citations - 994
Mario A. R. Dantas is an academic researcher from Universidade Federal de Juiz de Fora. The author has contributed to research in topics: Context (language use) & Grid. The author has an hindex of 12, co-authored 221 publications receiving 800 citations. Previous affiliations of Mario A. R. Dantas include University of Southampton & University of Illinois at Urbana–Champaign.
Papers
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Journal ArticleDOI
An approach for SDN traffic monitoring based on big data techniques
TL;DR: This paper proposes an approach based on a fine-grained Big Data monitoring method to collect and generate traffic statistics using counter values that can provide a more detailed view of network resource utilization.
Journal ArticleDOI
A Checkpoint of Research on Parallel I/O for High-Performance Computing
Francieli Zanon Boito,Eduardo C. Inacio,Jean Luca Bez,Philippe O. A. Navaux,Mario A. R. Dantas,Yves Denneulin +5 more
TL;DR: This survey article focuses on a traditional I/O stack, with a POSIX parallel file system, and aims at identifying the general characteristics of the field and the main current and future research topics.
Journal ArticleDOI
A survey into performance and energy efficiency in HPC, cloud and big data environments
TL;DR: This study indicates that around 56.4% of the papers reviewed offer contributions to performance and energy efficiency improvement, and the growing interest in this subject has a rate of 7.86% per year.
Proceedings ArticleDOI
Toward assessing Quality of Context parameters in a ubiquitous assisted environment
TL;DR: This paper provides an approach to assessing Quality of Context (QoC) parameters in a ubiquitous Ambient Assisted Living (ALL) environment and introduces the context management architecture used.
Journal ArticleDOI
FASTEN IIoT: An Open Real-Time Platform for Vertical, Horizontal and End-To-End Integration.
Felipe Schneider Costa,Silvia Modesto Nassar,Sergio Gusmeroli,Ralph Schultz,André Gustavo Scolari Conceição,Miguel G. Xavier,Fabiano Hessel,Mario A. R. Dantas +7 more
TL;DR: The FASTEN IIoT Platform is presented, which targets to provide a flexible, configurable, and open solution that acts as an interface between the shop floor and the industry 4.0 advanced applications and solutions.