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Leonardo Rebouças de Carvalho
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2020 – today
- 2024
- [j7]Leonardo Rebouças de Carvalho
, Bruno Kamienski, Aletéia P. F. Araújo:
Main FaaS Providers Behavior Under High Concurrency: An Evaluation with Orama Framework Distributed Architecture. SN Comput. Sci. 5(5): 541 (2024) - 2023
- [j6]Leonardo Rebouças de Carvalho
FaaS-Oriented Node.js Applications in an RPC Approach Using the Node2FaaS Framework. IEEE Access 11: 112027-112043 (2023) - [j5]Leonardo Rebouças de Carvalho
AFMC: An alignment framework for multiple computing services and providers. Concurr. Comput. Pract. Exp. 35(18) (2023) - [j4]Breno G. S. Costa, João Bachiega Jr., Leonardo Rebouças de Carvalho
Orchestration in Fog Computing: A Comprehensive Survey. ACM Comput. Surv. 55(2): 29:1-29:34 (2023) - [j3]João Bachiega Jr.
Computational Resource Allocation in Fog Computing: A Comprehensive Survey. ACM Comput. Surv. 55(14s): 336:1-336:31 (2023) - [j2]Leonardo Rebouças de Carvalho
Insights into the Performance of Function-as-a-Service Oriented Environments Using the Orama Framework. SN Comput. Sci. 4(3): 305 (2023) - [c11]Leonardo Rebouças de Carvalho, Bruno Kamienski, Aletéia P. F. Araújo:
FaaS Benchmarking over Orama Framework's Distributed Architecture. CLOSER 2023: 67-77 - 2022
- [j1]Breno G. S. Costa, João Bachiega Jr., Leonardo Rebouças de Carvalho
Monitoring fog computing: A review, taxonomy and open challenges. Comput. Networks 215: 109189 (2022) - [c10]Marcelo Augusto da Cruz Motta, Leonardo Rebouças de Carvalho, Michel Junio Ferreira Rosa, Aletéia Patrícia Favacho de Araújo:
Comparison of FaaS Platform Performance in Private Clouds. CLOSER 2022: 109-120 - [c9]João Bachiega Jr., Breno G. S. Costa, Leonardo Rebouças de Carvalho
From the Sky to the Ground: Comparing Fog Computing with Related Distributed Paradigms. CLOSER 2022: 158-169 - [c8]Leonardo Rebouças de Carvalho
Orama: A Benchmark Framework for Function-as-a-Service. CLOSER 2022: 313-322 - [c7]Leonardo Rebouças de Carvalho, Felipe L. S. Mendes, Jefferson Chaves, Marcos C. Lima, Flavio Elias Gomes de Deus, Aletéia P. F. Araújo, Flavio de Barros Vidal:
Deep-vacuity: A Proposal of a Machine Learning Platform based on High-performance Computing Architecture for Insights on Government of Brazil Official Gazettes. WEBIST 2022: 136-143 - [i1]Breno G. S. Costa, João Bachiega Jr., Leonardo Rebouças de Carvalho, Michel J. F. Rosa, Aletéia P. F. Araújo:
Monitoring Fog Computing: a Review, Taxonomy and Open Challenges. CoRR abs/2206.07091 (2022) - 2020
- [c6]Leonardo Rebouças de Carvalho
Performance Analysis of Main Public Cloud Big Data Services Processing Brazilian Government Data. CARLA 2020: 49-61 - [c5]Leonardo Rebouças de Carvalho
Performance Comparison of Terraform and Cloudify as Multicloud Orchestrators. CCGRID 2020: 380-389 - [c4]Leonardo Rebouças de Carvalho
Remote Procedure Call Approach using the Node2FaaS Framework with Terraform for Function as a Service. CLOSER 2020: 312-319 - [c3]Marcos C. Lima, Roberta Silva, Felipe Lopes de Souza Mendes, Leonardo Rebouças de Carvalho
Inferring about fraudulent collusion risk on Brazilian public works contracts in official texts using a Bi-LSTM approach. EMNLP (Findings) 2020: 1580-1588
2010 – 2019
- 2019
- [c2]Leonardo Rebouças de Carvalho
Framework Node2FaaS: Automatic NodeJS Application Converter for Function as a Service. CLOSER 2019: 271-278 - [c1]Klayton Castro, Gabriel R. D. Macedo, Aletéia P. F. Araújo, Leonardo Rebouças de Carvalho
Cloud.Jus: Architecture for Provisioning Infrastructure as a Service in the Government Sector. CLOSER 2019: 412-421
Coauthor Index
aka: Aletéia Patrícia Favacho de Araújo
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