Rong Rong

Florida International University School of Computing and Information Sciences

Lecture Information:
  • April 24, 2024
  • 11:37 AM
  • ECS: 243

Speaker Bio

Rong Rong is a Ph.D. candidate at the School of Computing and Information Sciences, Florida International University. She received a B.E. degree from Beihang University in China in 2006 and an M.S. degree from the Renmin University in China in 2009. Her research is in the area of network simulation and traffic modeling under the supervision of Dr. Jason Liu.


As the size of Internet increases, efficiently studying the behavior of the network becomes increasingly challenging. Scalability is critical for many applications subject to large-scale network-wide effects. Thus for exploring design space of future networks, an effective experimental testbed capable of accurately reproducing large-scale network behaviors would be highly valuable. Among existing network testbeds, physical and emulation testbeds can offer operational realism and real traffic, but are limited to inflexible configurations and physical constraints; simulation is easy for prototyping large and complex scenarios, but lacks realism. Currently there exists no testbed that can cover all important aspects of realism, scalability and flexibility.

We propose to augment existing physical testbeds with high performance simulation and traffic modeling. Such a hybrid testbed that can perform large-scale experiments, offer diverse network scenarios, and also maintain accurate representation of the operations of the target applications. In this thesis, we focus on three challenges of building such an experimental testbed. First is scalability. We need a high performance testbed capable of running large models on diverse high-end computing platforms. Second is fidelity. We need a testbed to run real target applications directly in a physical networking environment. Third is applicability. We need a testbed that can accommodate a wide range of applications, such as Future Internet applications.

To tackle these challenges, our research focuses on three areas: (1) high-performance simulation, (2) symbiotic fluid traffic modeling, and (3) experimental support for software-defined networking applications.