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Authored by researchers William L. Reiznautt and Nelson Fonseca of the Institute of Computing at the State University of Campinas (UNICAMP), this research paper presents H-DLAFR, a technological solution designed to manage dynamic link aggregation and traffic redistribution in networks that combine modern SDN (Software-Defined Networking) equipment with traditional switches.

SDN networks use an architecture that separates the control plane from the data plane, allowing forwarding policies to be programmed and managed centrally.

As a result, large networks—such as those of companies with geographically distributed branches—can simplify management, reduce operating costs, and facilitate the automation of changes and policies for data flow distribution.

Despite its advances, the full adoption of SDN still faces challenges in corporate and academic environments, especially due to the presence of traditional or legacy equipment that does not support SDN programmability or cannot be updated to incorporate this functionality. It is in this context that hybrid SDN networks have emerged, combining the programmability of SDN with the stability of traditional networks. In these networks, SDN equipment is deployed at strategic points, allowing for indirect control of legacy devices and the collection of metrics on the network’s overall behavior.

The gap that motivated this work was the lack of a solution that combines the programmability of SDN with the compatibility of traditional switches to enable dynamic aggregation and adaptive flow redistribution in hybrid networks. The model proposed in this article, called H-DLAFR (Hybrid Dynamic Link Aggregation and Flow Redistribution), was developed precisely to address this gap, offering a compatible, automated, and resilient approach to link aggregation in hybrid SDN networks.

Innovation

The project’s key innovation consists of using RARP frames to indirectly update the MAC address forwarding table—known as the FDB—in traditional switches.

In addition, the H-LARP policy periodically monitors link utilization and redistributes data flows based on observed conditions, reducing overloads and overcoming the limitations of the static load balancing used by LACP. Experimental tests confirm that this approach significantly increases aggregate throughput and infrastructure resilience, ensuring an efficient transition to programmable networks. Thus, the model offers automation and adaptive load balancing in heterogeneous network environments. In addition to the experimentally demonstrated gains in throughput and link utilization, the architecture incorporates fault detection and self-healing mechanisms.

The experiments were conducted in a combination of a virtualized environment and actual physical equipment.

The research, presented at SBRC 2026, is published at https://sol.sbc.org.br/index.php/sbrc/article/view/42278/42045

Sharing the application at the edge can cause latency issues. However, research by Professor Marcelo Fernandes of INCT ICoNIoT has shown that, depending on the control system, sharing is feasible

Historically, control systems in industrial plants (such as tanks in the chemical processing industry, industrial motors, production lines, and others) involved fixed, dedicated control equipment located near the plant. However, the vast majority of this equipment is undergoing a process of virtualization, becoming software. In modern edge computing architecture, this control equipment can be transformed into microservices in the form of applications running on edge servers. This transition offers a crucial advantage: the ability to share resources. Whereas physical equipment was previously required for each element of the plant (for example, one piece of equipment for each tank), the edge application can now be shared across multiple tanks. This leads to significant cost and energy savings.

However, the shift to shared microservices presents a new challenge: latency. Previously, the proximity of control equipment and industrial IoT devices ensured low latency. Sharing the application at the edge can introduce latency issues. However, research by Professor Marcelo Fernandes of INCT ICoNIoT has shown that, depending on the control system, sharing is feasible. For example, inherently slow systems, such as temperature or level control, tolerate latency and can be shared without issues. Marcelo Fernandes’s line of research, focused on edge computing and industrial IoT, aims precisely to use AI techniques for horizontal scaling. Horizontal scaling refers to the use of AI to automatically increase or decrease the number of these control applications, ensuring that the system continues to function properly.

Hypothesis Confirmed and Next Steps

Articles based on Dr. Fernandes’s research confirm the hypothesis that there are situations in which it is possible to share these control systems (emulating industrial plants) while ensuring they continue to function properly. The next step is crucial: using machine learning to perform horizontal scaling specifically in the context of industrial IoT plants. This is necessary because the parameters analyzed for horizontal scaling differ in each specific situation.

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Professor Marcelo Fernandes’ work also includes collaboration with Professor Debora Saade (UFF) in the field of Health, demonstrating the potential for exchange and interdisciplinary collaboration fostered by INCT ICoNIoT.

CSBC—the Brazilian Computer Society Conference—begins on the 19th and runs through July 23, and the full program is now available on the website.

This year, the conference features 10 main events and 17 satellite events. Organized by the Brazilian Computer Society (SBC), the leading scientific organization in this field in Brazil, this year’s conference is being organized by researchers Weverton Cordeiro and Alberto Egon Schaeffer Filho (UFRGS)—both affiliated with INCT ICoNIoT—who look forward to welcoming everyone in Gramado.

Social Role

Beyond being a scientific conference, CSBC fulfills a vital social role by bringing our community together to present results and strengthen relationships that drive innovation.

The conference helps professors, students, and professionals from across the country finally reconnect and collaborate. Each year, the conference sets a new challenge. For the 46th edition in 2026, the central theme chosen is: “Digital Transformation for a World in the Face of Climate Emergency.”

Learn more

Weverton Cordeiro and Alberto Egon Schaeffer Filho explain that this choice was motivated by recent climate events, such as the floods in Rio Grande do Sul and the heavy rains with severe impacts that recently occurred in Juiz de Fora, MG. In light of these scenarios, the field of computing proves to be an indispensable ally in the search for solutions, which include monitoring systems and high-precision sensors

 

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.

 

The project is the result of a collaboration among ICoNIoT researchers from four Brazilian universities and is among the nominees for the Best Paper Award at SBRC 2026

VAMOS! is the result of a collaboration between researchers Carnot Braun (State University of Campinas – UNICAMP), Daniel L. Guidoni (Federal University of Ouro Preto – UFOP), Eduardo Cerqueira (Federal University of Pará – UFPA), Joahannes B. D. da Costa (Federal University of São Paulo – UNIFESP), Leandro Villas (UNICAMP), and Allan M. Souza (UNICAMP).

The agent developed by the team, titled VAMOS (Vehicular Agent for Multi-Objective Optimization and Semantics), functions as an intelligent system capable of formulating personalized routes by interpreting the environmental context and the individual priorities of each user. It outperforms traditional navigation systems, which prioritize metric efficiency, such as time and distance, but fail to interpret more complex and context-dependent human intentions.

Unlike conventional navigation systems, this agent uses a Large Language Model (LLM) to suggest strategic stops, such as gas stations or grocery stores, based on continuous learning about the traveler’s profile. The technology’s unique feature lies in its ability to process complex information to optimize routes without the need for overly specific geographic commands.

The project faces the technical challenge of balancing robust processing on external servers with the feasibility of running smaller models directly on mobile devices.

Read the researchers’ paper published in the proceedings of SBRC 2026

The presentation of the SBRC Outstanding Achievement Award—Prof. Otto Carlos Muniz Bandeira Duarte—will take place during the Opening Ceremony of SBRC 2026, to be held on May 26, 2026, in Praia do Forte, Bahia.

Recognition

Prof. Edmundo’s name was chosen by a Selection Committee composed of the recipients of the same award over the past five years, in recognition of his entire career and contributions to the Brazilian scientific community in the fields of Computer Networks and Distributed Systems.

About the Award

The SBRC Outstanding Achievement Award was created in 2012 as part of the celebrations marking the SBRC’s 30th anniversary, and aims to honor members of the SBRC community who have distinguished themselves throughout their lives for their scientific contributions in the fields of computer networks and distributed systems, for their involvement in SBRC activities, and/or for services rendered to the benefit of the Brazilian computer networks and distributed systems community.

In 2022, the Outstanding Achievement Award was renamed the SBRC Prof. Otto Carlos Muniz Bandeira Duarte Outstanding Achievement Award. Otto held a bachelor’s degree in Electronic Engineering from UFRJ, a master’s degree in Electrical Engineering from Coppe/UFRJ, and a doctorate in Teleinformatics from the Ecole Nationale Supérieure des Télécommunications (ENST) in Paris, France. He became a Full Professor at UFRJ in 2003. He was recognized as a CNPq Level 1A Productivity Fellow and as a Scientist of Our State of Rio de Janeiro. He advised 17 doctoral theses, 55 master’s dissertations, and more than 180 undergraduate research projects. He had more than 350 articles published in peer-reviewed journals and conference proceedings.

Career of this Year’s Honoree

Prof. Edmundo is currently a Full Professor at the Institute of Computing at UNICAMP, the university where he earned his Ph.D. in Electrical Engineering in 1991. He has an extensive scientific output in the fields of Computer Networks and Distributed Systems, with over 6,000 citations, covering critical topics such as network management, cloud computing, and network virtualization. His academic reputation was recognized by UNICAMP’s Zeferino Vaz Award for Academic Recognition in 2004, and his work also includes coordinating research projects of national significance and collaborating with various research networks across the country, such as the National Institutes of Science and Technology (INCTs).

Prof. Edmundo has played a prominent role in organizing and structuring the SBRC, the leading event in the field in Brazil, having directly contributed to the technical and scientific quality of the Symposium over the course of several editions. In teaching, he contributes significantly to the training of high-level professionals and the mentoring of young researchers. In addition to teaching, he is actively involved in the scientific community, serving as a member of the Editorial Board of the Journal of Network and Systems Management (JNSM), published by Springer.