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 | 77 | 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 | 25 | 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 | 23 | 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 | 23 | 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 | 16 | 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 | 15 | 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 | 14 | 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 | 13 | 2020 |
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 | 11 | 2014 |
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 | 9 | 2023 |
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 | 9 | 2021 |
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 | 9 | 2016 |
A scalable platform for monitoring data intensive applications I Drăgan, G Iuhasz, D Petcu Journal of Grid Computing 17, 503-528, 2019 | 8 | 2019 |
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 | 8 | 2016 |
Applying self-* principles in heterogeneous cloud environments I Drăgan, TF Fortiş, G Iuhasz, M Neagul, D Petcu Cloud Computing: Principles, Systems and Applications, 255-274, 2017 | 7 | 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 | 7 | 2013 |
Monitoring of exascale data processing G Iuhasz, D Petcu 2019 IEEE International Conference on Advanced Scientific Computing (ICASC), 1-5, 2019 | 6 | 2019 |
Overview of machine learning tools and libraries D Pop, G Iuhasz Inst. e-Austria Timisoara, 0 | 5 | |
Dataset for anomaly detection in a production wireless mesh community network L Cerdà-Alabern, G Iuhasz Data in brief 49, 109342, 2023 | 3 | 2023 |
TUFA: A TOSCA extension for the specification of accelerator-aware applications in the Cloud Continuum A Spătaru, G Iuhasz, S Panica 2022 IEEE 46th Annual Computers, Software, and Applications Conference …, 2022 | 3 | 2022 |