activity
20222024
most citedRuntime data center temperature prediction using Grammatical Evolution techniques

43 citations · 75 across the 5 of their papers we have counts for

collaborators

7 papers

cs.DC2024

Efficient Training Approaches for Performance Anomaly Detection Models in Edge Computing Environments

Duneesha Fernando, Maria A. Rodriguez, Patricia Arroba +2

Microservice architectures are increasingly used to modularize IoT applications and deploy them in distributed and heterogeneous edge computing environments. Over time, these micro…

cs.DC202412 cited

Enhancing Regression Models for Complex Systems Using Evolutionary Techniques for Feature Engineering

Patricia Arroba, José L. Risco-Martín, Marina Zapater +2

This work proposes an automatic methodology for modeling complex systems. Our methodology is based on the combination of Grammatical Evolution and classical regression to obtain an…

cs.AR202420 cited

Green Adaptation of Real-Time Web Services for Industrial CPS within a Cloud Environment

Teresa Higuera, José L. Risco-Martín, Patricia Arroba +1

Managing energy efficiency under timing constraints is an interesting and big challenge. This work proposes an accurate power model in data centers for time-constrained servers in…

cs.DC2023

Heuristics and Metaheuristics for Dynamic Management of Computing and Cooling Energy in Cloud Data Centers

Patricia Arroba, José L. Risco-Martín, José M. Moya +1

Data centers handle impressive high figures in terms of energy consumption, and the growing popularity of Cloud applications is intensifying their computational demand. Moreover, t…

cs.DC2023

Mercury: A modeling, simulation, and optimization framework for data stream-oriented IoT applications

Román Cárdenas, Patricia Arroba, Roberto Blanco +3

The Internet of Things is transforming our society by monitoring users and infrastructures' behavior to enable new services that will improve life quality and resource management.…

cs.SE2023

The DEVStone Metric: Performance Analysis of DEVS Simulation Engines

Román Cárdenas, Kevin Henares, Patricia Arroba +2

The DEVStone benchmark allows us to evaluate the performance of discrete-event simulators based on the DEVS formalism. It provides model sets with different characteristics, enabli…