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ORCIDDionatra F. Kirchoff
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Journal Articles
- 2024
[j4]Dionatra F. Kirchoff, Vinícius Meyer, Rodrigo N. Calheiros, César A. F. De Rose:
Evaluating machine learning prediction techniques and their impact on proactive resource provisioning for cloud environments. J. Supercomput. 80(15): 21920-21951 (2024)- 2022
- [j3]Vinícius Meyer
, Matheus L. da Silva, Dionatra F. Kirchoff, César A. F. De Rose:
IADA: A dynamic interference-aware cloud scheduling architecture for latency-sensitive workloads. J. Syst. Softw. 194: 111491 (2022) - 2021
- [j2]Vinícius Meyer, Dionatra F. Kirchoff, Matheus L. da Silva, César A. F. De Rose:
ML-driven classification scheme for dynamic interference-aware resource scheduling in cloud infrastructures. J. Syst. Archit. 116: 102064 (2021) - 2019
- [j1]Uillian L. Ludwig, Miguel G. Xavier, Dionatra F. Kirchoff, Ian B. Cezar, César A. F. De Rose:
Optimizing multi-tier application performance with interference and affinity-aware placement algorithms. Concurr. Comput. Pract. Exp. 31(18) (2019)
Conference and Workshop Papers
- 2020
- [c5]Vinícius Meyer, Uillian L. Ludwig, Miguel G. Xavier, Dionatra F. Kirchoff, César A. F. De Rose:
Towards Interference-Aware Dynamic Scheduling in Virtualized Environments. JSSPP 2020: 1-24 - [c4]Vinícius Meyer, Dionatra F. Kirchoff, Matheus L. da Silva, César A. F. De Rose:
An Interference-Aware Application Classifier Based on Machine Learning to Improve Scheduling in Clouds. PDP 2020: 80-87 - [c3]Matheus L. da Silva, Vinícius Meyer, Dionatra F. Kirchoff, Joaquim Francisco Santos Neto, Renata Vieira, César A. F. De Rose:
Evaluating the performance and improving the usability of parallel and distributed Word Embeddings tools. PDP 2020: 201-206 - 2019
- [c2]Vinícius Meyer, Miguel G. Xavier, Dionatra F. Kirchoff, Rodrigo da Rosa Righi, César A. F. De Rose:
Performance and Cost Analysis between Elasticity Strategies over Pipeline-structured Applications. CLOSER 2019: 404-411 - [c1]Dionatra F. Kirchoff, Miguel G. Xavier, Juliana Mastella, César A. F. De Rose:
A Preliminary Study of Machine Learning Workload Prediction Techniques for Cloud Applications. PDP 2019: 222-227
Coauthor Index
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