Patricia Arroba
Zitiert von
Zitiert von
Dynamic Voltage and Frequency Scaling‐aware dynamic consolidation of virtual machines for energy efficient cloud data centers
P Arroba, JM Moya, JL Ayala, R Buyya
Concurrency and Computation: Practice and Experience 29 (10), e4067, 2017
DVFS-aware consolidation for energy-efficient clouds
P Arroba, JM Moya, JL Ayala, R Buyya
2015 International Conference on Parallel Architecture and Compilation (PACT …, 2015
Runtime data center temperature prediction using grammatical evolution techniques
M Zapater, JL Risco-Martín, P Arroba, JL Ayala, JM Moya, R Hermida
Applied Soft Computing 49, 94-107, 2016
Server power modeling for run-time energy optimization of cloud computing facilities
P Arroba, JL Risco-Martín, M Zapater, JM Moya, JL Ayala, K Olcoz
Energy Procedia 62, 401-410, 2014
Energy-conscious optimization of Edge Computing through Deep Reinforcement Learning and two-phase immersion cooling
S Pérez, P Arroba, JM Moya
Future Generation Computer Systems 125, 891-907, 2021
Data augmentation through multivariate scenario forecasting in Data Centers using Generative Adversarial Networks
J Pérez, P Arroba, JM Moya
Applied Intelligence 53 (2), 1469-1486, 2023
Enhancing regression models for complex systems using evolutionary techniques for feature engineering
P Arroba, JL Risco-Martín, M Zapater, JM Moya, JL Ayala
Journal of Grid Computing 13, 409-423, 2015
A methodology for developing accessible mobile platforms over leading devices for visually impaired people
P Arroba, JC Vallejo, Á Araujo, D Fraga, JM Moya
Ambient Assisted Living: Third International Workshop, IWAAL 2011, Held at …, 2011
Green adaptation of real-time web services for industrial CPS within a cloud environment
MT Higuera-Toledano, JL Risco-Martín, P Arroba, JL Ayala
IEEE Transactions on Industrial Informatics 13 (3), 1249-1256, 2017
Mercury: A modeling, simulation, and optimization framework for data stream-oriented IoT applications
R Cárdenas, P Arroba, R Blanco, P Malagón, JL Risco-Martín, JM Moya
Simulation Modelling Practice and Theory 101, 102037, 2020
Heuristics and metaheuristics for dynamic management of computing and cooling energy in cloud data centers
P Arroba, JL Risco‐Martín, JM Moya, JL Ayala
Software: Practice and Experience 48 (10), 1775-1804, 2018
A novel energy-driven computing paradigm for e-health scenarios
M Zapater, P Arroba, JL Ayala, JM Moya, K Olcoz
Future Generation Computer Systems 34, 138-154, 2014
Modeling and simulation of smart grid-aware edge computing federations
R Cárdenas, P Arroba, JL Risco-Martín, JM Moya
Cluster Computing 26 (1), 719-743, 2023
Predictive GPU-based ADAS management in energy-conscious smart cities
S Pérez, J Pérez, P Arroba, R Blanco, JL Ayala, JM Moya
2019 ieee international smart cities conference (isc2), 349-354, 2019
Thermal prediction for immersion cooling data centers based on recurrent neural networks
J Pérez, S Pérez, JM Moya, P Arroba
International Conference on Intelligent Data Engineering and Automated …, 2018
xDEVS: A toolkit for interoperable modeling and simulation of formal discrete event systems
JL Risco‐Martín, S Mittal, K Henares, R Cardenas, P Arroba
Software: Practice and Experience 53 (3), 748-789, 2023
Proactive power and thermal aware optimizations for energy-efficient cloud computing
PA Garcia
Universidad Politécnica de Madrid, 2017
A trust and reputation system for energy optimization in cloud data centers
I Aransay, M Zapater, P Arroba, JM Moya
2015 IEEE 8th International Conference on Cloud Computing, 138-145, 2015
Bringing AI to the edge: A formal M&S specification to deploy effective IoT architectures
R Cárdenas, P Arroba, JL Risco Martin
Journal of Simulation 16 (5), 494-511, 2022
Energy‐efficiency and sustainability in new generation cloud computing: A vision and directions for integrated management of data centre resources and workloads
R Buyya, S Ilager, P Arroba
Software: Practice and Experience 54 (1), 24-38, 2024
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