Iuhasz Gabriel
Citat de
Citat de
Dice: Quality-driven development of data-intensive cloud applications
G Casale, D Ardagna, M Artac, F Barbier, E Di Nitto, A Henry, G Iuhasz, ...
2015 IEEE/ACM 7th International Workshop on Modeling in Software Engineering …, 2015
Neuroevolution based multi-agent system for micromanagement in real-time strategy games
I Gabriel, V Negru, D Zaharie
Proceedings of the fifth balkan conference in informatics, 32-39, 2012
An overview of monitoring tools for big data and cloud applications
G Iuhasz, I Dragan
Symbolic and Numeric Algorithms for Scientific Computing (SYNASC), 2015 17th …, 2015
Neural network predictions of stock price fluctuations
G Iuhasz, M Tirea, V Negru
2012 14th International Symposium on Symbolic and Numeric Algorithms for …, 2012
Architecture of a scalable platform for monitoring multiple big data frameworks
G Iuhasz, D Pop, I Dragan
Scalable Computing: Practice and Experience 17 (4), 313-321, 2016
Tuning logstash garbage collection for high throughput in a monitoring platform
DN Doan, G Iuhasz
2016 18th International Symposium on Symbolic and Numeric Algorithms for …, 2016
Support services for applications execution in multi-clouds environments
D Pop, G Iuhasz, C Craciun, S Panica
2016 IEEE international conference on autonomic computing (ICAC), 343-348, 2016
M3at: Monitoring agents assignment model for data-intensive applications
V Kashansky, D Kimovski, R Prodan, P Agrawal, F Marozzo, G Iuhasz, ...
2020 28th Euromicro International Conference on Parallel, Distributed and …, 2020
Distributed platforms and cloud services: Enabling machine learning for big data
D Pop, G Iuhasz, D Petcu
Data Science and Big Data Computing: Frameworks and Methodologies, 139-159, 2016
Neuroevolution based multi-agent system with ontology based template creation for micromanagement in real-time strategy games
I Gabriel, V Negru, D Zaharie
Information Technology and Control 43 (1), 98-109, 2014
Serrano: Transparent application deployment in a secure, accelerated and cognitive cloud continuum
A Kretsis, P Kokkinos, P Soumplis, JJV Olmos, M Fehér, M Sipos, ...
2021 IEEE International Mediterranean Conference on Communications and …, 2021
On processing extreme data
D Petcu, G Iuhasz, D Pop, D Talia, J Carretero, R Prodan, T Fahringer, ...
Scalable Computing. Practice and Experience 16 (4), 467-489, 2016
A scalable platform for monitoring data intensive applications
I Drăgan, G Iuhasz, D Petcu
Journal of Grid Computing 17, 503-528, 2019
Applying self-* principles in heterogeneous cloud environments
I Drăgan, TF Fortiș, G Iuhasz, M Neagul, D Petcu
Cloud Computing: Principles, Systems and Applications, 255-274, 2017
Data mining considerations for knowledge acquisition in real time strategy games
G Iuhasz, VI Munteanu, V Negru
2013 IEEE 11th International Symposium on Intelligent Systems and …, 2013
Monitoring of exascale data processing
G Iuhasz, D Petcu
2019 IEEE International Conference on Advanced Scientific Computing (ICASC), 1-5, 2019
Overview of machine learning tools and libraries
D Pop, G Iuhasz
Inst. e-Austria Timisoara, 0
Anomaly detection for fault detection in wireless community networks using machine learning
L Cerdà-Alabern, G Iuhasz, G Gemmi
Computer Communications 202, 191-203, 2023
Load balancing for multi-cloud
G Iuhasz, P Jamshidi, W Wang, G Casale
Model-Driven Development and Operation of Multi-Cloud Applications: The …, 2017
Run-time adaptation policies
G Casale, F Kalo, JF Pérez, W Wang, D Ardagna, M Ciavotta, G Iuhasz
MODAClouds EU Project Deliverable, 2014
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