Algorithms and Graph Based Models
The field of Graph Theory studies the relationships between elements, called nodes, and their connections, known as edges. This area encompasses models ranging from technological networks to social and air transportation networks. Its main subfields include Network Science, which analyzes interactions in complex systems, and Computer Networks, which provide the technological infrastructure for global communication.
Network Science investigates how the structure and dynamics of connections influence the global behavior of a network. Topics such as centrality, robustness, and structural patterns are analyzed to better understand social, economic, and biological networks. The growth of technology and the explosion of data in recent decades have further increased the relevance of this field.
In Computer Networks, defining the network topology is essential for efficient monitoring. This process can be modeled as an optimization problem or analyzed as a Complex Network, using graph-theoretic concepts to study its properties and performance. Moreover, infrastructure management and data communication rely on specific protocols tailored to different applications, such as environmental monitoring, mobile networks, and biomedical systems. The efficiency of these protocols is evaluated using metrics such as packet delivery rate, network throughput, and energy consumption.
This project aims to develop graph-based applications across various domains, combining computational simulation with practical experiments. It also seeks to improve the design and communication within these graph structures, exploring new protocols to make information transmission more efficient and resilient.
Faculty Members Involved:
- Diego Nunes Brandão (coordinator)
- Felipe da Rocha Henriques
- Glauco Fiorott Amorim
- Helga Dolorico Balbi
- Laura Silva de Assis