About / Short Bio

I have a degree in Mechanical Engineering from the Federal University of Rio Grande do Sul (UFRGS in 1978), a master's degree in Computer Science from UFRGS (1986) and a PhD in Informatics - Université de Grenoble I (Scientifique Et Medicale - Joseph Fourier) (1991). I obtained my retirement in 2023 when I was a full professor at the Federal University of Rio Grande do Sul. I currently work as a visiting professor in the Postgraduate Program in Computing at UFRGS. I have experience in the area of ​​Computer Science, with an emphasis on Distributed Systems, having worked mainly in the following themes: EAD, IoT and FOG/EDGE, Big Data, Pervasive Computing (ubiquitous), Cloud Computing, Grid and Voluntary Computing, and support for multiplayer games, with an emphasis on building middleware and tools for these areas of computing and applying AI techniques. I previously worked on the topics of logic programming and parallel Prolog (doctorate topic).

WordPress Page (in progress): https://claudiogeyer.wordpress.com/

Contact Info

E-mail

geyer at inf.ufrgs.br
claudio.geyer at gmail.com

Teaching Activities

Graduate course

CMP258

Development of Big Data, Cloud and Fog/EDGE Applications

Research Areas

Distributed Systems
Distributed Systems is my main area of ​​research. Over time, several sub-areas were created and some later lost part of their appeal. However, the main themes (or problems), defined in the 70s to 90s by authors such as Andrew Tanenbaum, remain central to most current research projects. An initial list of these problems is below:

- Resource Management;
- Scalability;
- Communication and Latency;
- Heterogeneity;
- Interoperability;
- Data Consistency;
- Fault Tolerance;
- Autonomous and Intelligent Systems.

Some of the subareas already researched in the group were:

- Distributed Operating Systems;
- Grid Computing;
- Distributed Servers for Multiplayer Games;
- Ubiquitous Computing;
- Tools to support Education.

Currently, the main subareas of the group are:

- Big Data, both batch and streaming;
- IoT including Fog, Edge, and Cloud;
- Autonomous and Intelligent Systems;
- Federated Learning (Distributed Machine Learning);
- Applications of these areas in Smart Cities, Healthcare, and other applied areas.

Some of the research problems in these areas are currently being addressed by the group of students:

- Resource management and task scheduling in the areas of IoT + Fog / Edge and Cloud;
- Resource management in framework kernels in the areas of Big Data and IoT: memory, network, I/O, …;
- Use of Machine Learning and Federated Learning in the healthcare area, such as in the analysis of Alzheimer's images and Sepsis data;
- Communication protocols for IoT aiming at better efficiency with adaptation to the context;
- Analysis of fake news data: evolution, social areas, geographic areas, …;
- Resource monitoring using Blockchain and other current techniques.

The following texts and presentations detail the research problems and the recent and ongoing activities in the above areas:

* Mamonas Project initial version:

** Personal project registered at UFRGS;
** 2021 version;
** Focus on autonomous and intelligent systems in the areas of Big Data and IoT;
** LinkPortugueseVersion: https://tinyurl.com/bdfnp95s
** LinkEnglishVersion (in progress):

* Mamonas Project, 2024 extension version;

** Also contains a list of individual works in progress;
** LinkPortugueseVersion: https://tinyurl.com/ytxj8yvs
** LinkEnglishVersion (in progress):


* Report of complete works in Big Data;
** Link: https://tinyurl.com/3beumzet

* Report of complete works in Ubicomp (IoT):
** Link: https://tinyurl.com/yw2t3h8y

* Presentation (slides) of the areas and works of the group;
** Link: https://tinyurl.com/ykfas5sz

Big Data

IoT