Jason Liu

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Research Profile

Dr. Jason Liu’s research focuses on parallel and distributed simulation, high-performance modeling and simulation of computer systems and computer networks.  A central theme of his research is to investigate enabling technologies for building high-fidelity high-performance simulation and emulation testbeds to facilitate discoveries and innovations of large-scale complex computer networks and computer systems.

Specific areas of Dr. Liu’s research include:

  • Enabling scalable and high-performance parallel and distributed simulation on high-end computing platforms. Dr. Liu’s research in parallel simulation has concentrated on advancing technologies for executing large-scale simulation models in parallel and distributed environments. Parallel simulation is an area crosscutting between modeling, simulation, and high-performance computing areas. Dr. Liu’s research focuses on development of high-performance simulation engines and design of efficient parallel algorithms to support massive-scale simulation experiments on modern high-end computing platforms. The parallel simulation techniques can readily be applied in studies of cyber-security systems, intrusion detection, cyber-security and cyber-defense assessment, and so on.
  • Designing network testbeds based on hybrid simulation, emulation, and high-performance modeling techniques. The ability to conduct high-fidelity high-performance experiments is critical to studying complex large-scale cyber systems, such as the cross-domain aspects of autonomous decision support systems, theeffectiveness of new defensive technologies for countering malicious cyber attacks, and so on. Dr. Liu’s research in this area consists of: 1) applying real-time techniques for immersive network modeling; 2) developing interactive simulation techniques supporting human-in-the-loop and machine-in-the-loop studies; 3) designing efficient models for representing large-scale network behaviors; and 4) designing techniques to facilitate efficient interactions between mathematical models, simulations, emulation, and physical systems.
  • Applying high-performance modeling, parallel simulation, and interactive simulation andliu-bgp emulation techniques in various specific areas of research, including: 1) cyber-security systems, intrusion detection, security scenario analytics, cyber defense and training; 2) cyber-physical systems, smart grids, sensor networks, mission control, multi-model multi-environmentsystems, composite models, system of systems; 3) computer systems, scientific computing, parallel applications, parallel file systems, data center resource management, scheduling, data center networking; 4) wireless communication networks, cellular systems, mobile computing; and 5) other fields, including social networks, transportation systems, aviation, disaster response, and decision support systems.

Previous Accomplishments

  • Dr. Liu’s research has been funded by DARPA, NSF, and Raytheon BBN Technologies.
  • Awards: NSF Career Award.
  • Collaborations: Information Trust Institute at University of Illinois, University of Massachusetts, Los Alamos National Laboratory, Oak Ridge National Laboratory, Sandia National Laboratories.

Relevant Publications

  1. Liu, Jason, and Rong Rong. “Hierarchical Composite Synchronization.” Principles of Advanced and Distributed Simulation (PADS), 2012 ACM/IEEE/SCS 26th Workshop on. IEEE, 2012.
  2. Van Vorst, N., M. Erazo, and J. Liu. PrimoGENI for hybrid network simulation and emulation experiments in GENI. Journal of Simulation 6.3 (2012): 179-192.
  3. Van Vorst, Nathanael, and Jason Liu. Realizing Large-Scale Interactive Network Simulation via Model Splitting. Principles of Advanced and Distributed Simulation (PADS), 2012 ACM/IEEE/SCS 26th Workshop on. IEEE, 2012.
  4. Van Vorst, Nathanael, and Jason Liu. Realizing Large-Scale Interactive Network Simulation via Model Splitting. Principles of Advanced and Distributed Simulation (PADS), 2012 ACM/IEEE/SCS 26th Workshop on. IEEE, 2012.
  5. Van Vorst, Nathanael, Ting Li, and Jason Liu. How low can you go? Spherical routing for scalable network simulations. Modeling, Analysis & Simulation of Computer and Telecommunication Systems (MASCOTS), 2011 IEEE 19th International Symposium on. IEEE, 2011.
  6. Liu, Jason, and Yue Li. Parallel hybrid network traffic models. Simulation 85.4 (2009): 271-286.
  7. Erazo, M. A., Li, T., Liu, J., & Eidenbenz, S. (2012, June). Toward comprehensive and accurate simulation performance prediction of parallel file systems. In Dependable Systems and Networks (DSN), 2012 42nd Annual IEEE/IFIP International Conference on (pp. 1-12). IEEE.
  8. Li, Yue, Michael Liljenstam, and Jason Liu. Real-time security exercises on a realistic interdomain routing experiment platform. In Proceedings of the 2009 ACM/IEEE/SCS 23rd Workshop on Principles of Advanced and Distributed Simulation. IEEE Computer Society, 2009.
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