Microservices: A Mapping Study for Internet of Things Solutions. - Cleber Jorge Lira de Santana; Brenno de Mello Alencar; Cássio V. S. Prazeres (NCA, 2018)

SOFT-IoT Platform in Fog of Things. - Leandro José Silva Andrade; Cleber Jorge Lira de Santana; Brenno Mello; Andressa Andrade; António Coutinho; Fabíola Greve; Cássio V. S. Prazeres (WebMedia, 2018)

Reactive microservices for the internet of things: a case study in fog computing. - Cleber Jorge Lira de Santana; Brenno de Mello Alencar; Cássio Vinicius Serafim Prazeres (SAC, 2019)

A reliable architecture based on reactive microservices for IoT applications. - Cleber Jorge Lira de Santana; Leandro José Silva Andrade; Brenno Mello; Ernando Batista; José Vitor Sampaio; Cássio V. S. Prazeres (WebMedia, 2019)

FoT-Stream: A Fog platform for data stream analytics in IoT. - Brenno de Mello Alencar; Ricardo Araújo Rios; Cleber Jorge Lira de Santana; Cássio V. S. Prazeres (Comput. Commun., 2020)

FoT-Rules: A Semantic Rule-based Approach for Smart Spaces Through Fog of Things. - Cleber Jorge Lira de Santana; Ernando Batista; Brenno Mello; Cássio V. S. Prazeres (Int. J. Semantic Comput., 2021)

Data interplay: A model to optimize data usage in the Internet of Things. - Leandro José Silva Andrade; Cleber Jorge Lira de Santana; Brenno de Mello Alencar; Claudio Silva Jr.; Cássio V. S. Prazeres (Softw. Pract. Exp., 2023)

Fog-DeepStream: A new approach combining LSTM and Concept Drift for data stream analytics on Fog computing. - Brenno de Mello Alencar; João Paulo Canário; Ruivaldo Lobão-Neto; Cássio V. S. Prazeres; Abert Bifet; Ricardo Araújo Rios (Internet Things, 2023)

Fast Learning Enabled by In-Network Drift Detection. - Bruno Missi Xavier; Magnos Martinello; Celio Trois; Brenno de Mello Alencar; Ricardo Araújo Rios (APNet, 2024)

A new intelligent scheduler to improve reactive OpenFlow communication in SDN-based IoT data streams. - Ernando Batista; Brenno de Mello Alencar; Eliabe Silva; João Canário; Ricardo Araújo Rios; Schahram Dustdar; Gustavo B. Figueiredo; Cássio V. S. Prazeres (Discov. Internet Things, 2024)

RMIDDM: an unsupervised and interpretable concept drift detection method for data streams. - Ruivaldo Lobão-Neto; Brenno de Mello Alencar; Heitor Murilo Gomes; Albert Bifet; João Gama 001; Guilherme Weigert Cassales; Ricardo Araújo Rios (Data Min. Knowl. Discov., 2025)