Cloud, Fog or Edge: Where to Compute? RP Dragi Kimovski, Roland Mathá, Josef Hammer, Narges Mehran, Hermann Hellwagner IEEE Internet Computing, 2021 | 77* | 2021 |
The Workflow Trace Archive: Open-Access Data from Public and Private Computing Infrastructures L Versluis, R Mathá, S Talluri, T Hegeman, R Prodan, E Deelman, A Iosup IEEE Transactions on Parallel and Distributed Systems 31 (9), 2170-2184, 2020 | 33 | 2020 |
ComplexCTTP: complexity class based transcoding time prediction for video sequences using artificial neural network A Zabrovskiy, P Agrawal, R Mathá, C Timmerer, R Prodan 2020 IEEE Sixth International Conference on Multimedia Big Data (BigMM), 316-325, 2020 | 19 | 2020 |
Simulation of a workflow execution as a real cloud by adding noise R Mathá, S Ristov, R Prodan Simulation Modelling Practice and Theory 79, 37-53, 2017 | 15 | 2017 |
Analysing the performance instability correlation with various workflow and cloud parameters S Ristov, R Mathá, R Prodan 2017 25th Euromicro International Conference on Parallel, Distributed and …, 2017 | 15 | 2017 |
Where to encode: A performance analysis of x86 and arm-based amazon ec2 instances R Mathá, D Kimovski, A Zabrovskiy, C Timmerer, R Prodan 2021 IEEE 17th International Conference on eScience (eScience), 118-127, 2021 | 14 | 2021 |
Simplified Workflow Simulation on Clouds based on Computation and Communication Noisiness R Mathá, S Ristov, T Fahringer, R Prodan IEEE Transactions on Parallel and Distributed Systems 31 (7), 1559-1574, 2020 | 14 | 2020 |
Multi-objective service oriented network provisioning in ultra-scale systems D Kimovski, S Ristov, R Mathá, R Prodan Euro-Par 2017: Parallel Processing Workshops: Euro-Par 2017 International …, 2018 | 8 | 2018 |
A new model for cloud elastic services efficiency S Ristov, R Mathá, D Kimovski, R Prodan, M Gusev International Journal of Parallel, Emergent and Distributed Systems 34 (6 …, 2019 | 5 | 2019 |
A simplified model for simulating the execution of a workflow in cloud R Mathá, S Ristov, R Prodan European Conference on Parallel Processing, 319-331, 2017 | 3 | 2017 |
Autotuning of exascale applications with anomalies detection D Kimovski, R Mathá, G Iuhasz, F Marozzo, D Petcu, R Prodan Frontiers in big Data 4, 657218, 2021 | 2 | 2021 |
The Workflow Trace Archive: Open-Access Data from Public and Private Computing Infrastructures--Technical Report L Versluis, R Mathá, S Talluri, T Hegeman, R Prodan, E Deelman, A Iosup arXiv preprint arXiv:1906.07471, 2019 | 2 | 2019 |
TOWARDS A REALISTIC CLOUD SIMULATION R Mathá UNIVERSITY OF INNSBRUCK, 2020 | | 2020 |
PDP 2019 I Colonnelli, N Mehran, T Cojean, E Carlini, D Spataro, MV Avolio, ... | | |
PDP 2017 E Agullo, MV Avolio, I Azimi, S Barbhuiya, E Barlaskar, A Bolotov, C Cao, ... | | |
PDP 2018 A De Rango, A Namazi, A Douma, A Tomas, A Lounis, AF Gil, A Esnard, ... | | |