Month: June 2026

The presentation will be titled ‘The Computing Continuum: Beyond Cloud and Edge Intelligence’

With the combination of Internet of things, edge, and cloud computing, computing services can be scattered over a set of computing resources that encompass everything between users’ devices and, including intermediate computing infrastructure deployed in between. The evolving networking technologies promote enhanced bandwidth and data transmission capacity with lower delays, which enables distributed computing resources to be faced as an entangled, distributed heterogeneous platform. This continuum of computing capacity can be used to process large amounts of data with reduced response times. However, creating a seamless distributed computing infrastructure and managing its resources to optimize applications with widely heterogeneous requirements is still a challenge, even after decades of research. The rise of distributed machine learning techniques adds more complexity but also brings additional mechanisms to address this problem. In this talk, I will present an overview of the resource allocation problem, focusing on aspects that can help build an Intelligent Computing Continuum.

The speaker

Luiz Bittencourt is an Associate Professor at Universidade Estadual de Campinas (UNICAMP), Brazil. Luiz was awarded with the IEEE ComSoc Latin America Young Professional Award in 2013. He acts on the organization of several conferences in the cloud and edge computing topics, and in several technical program committees. He served as associate editor for the IEEE Cloud Computing Magazine, and currently serves as AE for the Computers and Electrical Engineering and the Internet of Things journals, for the Journal of Network and Systems Management, and for IEEE Networking Letters. His main interests are in resource management and scheduling in cloud, edge, and fog computing, and their synergy towards an intelligent computing continuum through distributed machine learning techniques.

The 2026 edition of CSBC will feature 10 main events and 16 satellite events, covering different fields and levels of education.

Highlights include the Computer Science Update Conference (JAI), Women in Information Technology (WIT), the Thesis and Dissertation Competition (CTD), the National Computing Conference of Federal Institutes (ENCompIF), and COMPUTEC.

This diversity allows for the participation of a wide range of audiences, from students in their early stages of education to researchers and professionals engaged in advanced discussions on technology, the market, and management.

CSBC 2026 will be held July 19–23 in Gramado. Learn more

The 44th Brazilian Symposium on Computer Networks and Distributed Systems (SBRC 2026) was held in Praia do Forte, Bahia, from May 25 to 29, 2026. On the 27th, our INCT ICoNIoT workshop took place.

The meeting, led by Eduardo Cerqueira (UFPA), featured keynote speaker Torsten Braun from the University of Bern, as well as ICoNIoT researchers Carlos Kamienski (UFABC), Flavia Delicato (UFF), Marcelo Fernandes (UFRN), Allan Souza (UNICAMP), Everton Cavalcante (UFRN), Luiz Fernando Bittencourt (UNICAMP), Edmundo Madeira (UNICAMP), Rafael Lopes (UECE), Augusto Neto (UFRN), and Carlos Trujillo (UNICAMP).

During the event, progress on the projects was presented, and new opportunities for collaboration were opened up.

It was a highly successful moment for our INCT. Check out the video!

 

The 44th Brazilian Symposium on Computer Networks and Distributed Systems (SBRC 2026) was held in Praia do Forte, Bahia, from
May 25 to 29, 2026. In addition to the great success of our workshop, we are also celebrating several achievements by our team:

. The paper “Agent VAMOS! Semantic Context-Aware Vehicle Route Planning with LLM Agents” by Carnot Braun, Daniel Ludovico Guidoni, Eduardo Coelho Cerqueira, Joahannes Bruno Dias da Costa, Leandro Villas, and Allan Mariano de Souza received an Honorable Mention in the Main Track of SBRC 2026.

. The doctoral thesis titled “Overload Management Techniques
and Resource Allocation for Machine-Type Mass Communication in 3GPP Access Networks” by Tiago Pedroso (UNICAMP), and supervised by Prof. Nelson Fonseca (UNICAMP, and general coordinator of ICoNIoT), received an Honorable Mention in the Thesis and Dissertation Contest (CTD) at SBRC 2026.

. The master’s thesis titled “Collision Detection and
Prioritization in Intelligent mMTC Random Access in Cellular
IoT Networks”, authored by Giancarlo Maldonado Cardenas and supervised by professors Nelson L.S. da Fonseca and Carlos A. Astudillo, was awarded
an honorable mention in the Thesis and Dissertation Contest (CTD) at SBRC 2026.

. The paper “Safe Control and Collision Avoidance in Dense Drone Traffic
via Reinforcement Learning,” by Henrique J. Felisardo dos
Santos, Israel da Silva Barros, Luiz Fernando Bittencourt, Carlos
Kamienski, and Fabíola M. C. de Oliveira, received an honorable mention at the Urban Computing Workshop (CoUrb).

. The paper “Self-Supervised Learning for Early Preamble Collision
Detection in Cellular IoT Networks”, authored by Daniela M.
Casas-Velasco, Diogo Maciel Cunha, Marco Aurelio Guerra Pedroso,
Giancarlo Maldonado Cardenas, Carlos Alberto Astudillo Trujillo, and Nelson Fonseca, received an honorable mention at the 1st Workshop on Artificial Intelligence for Computer Networks (WIARC) at SBRC 2026.

. The paper “A Performance Comparison of Authentication and Authorization Patterns for Microservices Applications,” by Rafael Freitas Cardoso (UFRGS) and Jeferson Campos Nobre (UFRGS), received an honorable mention at the WGRS – 31st Workshop on Network and Service Management and Operation at SBRC 2026.

The K-alibra Agent is a Language Model (LM)-based orchestrator designed to dynamically adjust the number of participating clients in each round of Federated Learning (FL). It was created to overcome the rigidity of traditional static algorithms, which typically use a fixed number of clients, a practice that can lead to inefficiency or network overload.

The project was developed through a partnership between researchers from the State University of Campinas (UNICAMP), the Federal University of Pará (UFPA), and the Federal University of Minas Gerais (UFMG), all of which are part of ICoNIoT. They are: Rafael O. Jarczewski (UNICAMP), Eduardo Cerqueira (UFPA), Antonio Loureiro (UFMG), Leandro A. Villas (UNICAMP), and Allan de Souza (UNICAMP). It is published in the proceedings of SBRC 2026 and can be read in full here.

Federated Learning (FL) is a way to train artificial intelligence securely, since each person’s data remains protected on their own devices, without needing to be sent to a central server. The problem is that this process tends to use a lot of data and becomes difficult to manage when there are many users.

Currently, to address this issue, systems select which devices will participate in the training. However, these systems are “stubborn”: they tend to always use the same number of devices, without adjusting that number based on current needs. This causes the process to waste resources or take longer to learn.

To overcome this rigidity, K-Agent was created. It functions as an intelligent “boss” (using language models similar to those behind AI chatbots) that dynamically decides how many devices should participate in each stage.

It works in three steps:

1. It assesses the current state of the training.
2. It reasons to find the best strategy.
3. It acts by determining the optimal number of participants.

Tests have shown that K-Agent is highly efficient: it can reduce internet usage by between 44.4% and 59% compared to traditional methods, while maintaining stable, high-quality learning. Additionally, it can explain the reasoning behind its decisions, making the system more transparent for developers.

The project has been published in the proceedings of SBRC 2026 and can be read in full here.