A Research and Educational Framework to Advance Disaster Information Management in Computer Science PhD Programs
Project Summary:
The objective of this project is to provide an integrated research and educational framework that will advance disaster information management in Florida International University’s (FIU) School of Computing and Information Sciences (SCIS) Computer Science PhD degree program. The outcomes are expected in three areas: (1) increased graduate degrees awarded with Homeland Security-related Science, Technology, Engineering, and Mathematics (HS-STEM) related knowledge and skills, (2) engaging early career faculty to pursue HS-STEM research and education activities leveraging senior faculty research agenda in disaster information management, and (3) to enhance our computer science (CS) doctoral degree program course curriculum in areas relevant to HS-STEM. The pursuit of these objectives combined will create a sustainable and replicable research and education program that will create notoriety for FIU in the area of HS-STEM related expertise and will promote further research study at other HS-STEM interested institutions.
Investigators
- Dr. Shu-Ching Chen
- Dr. Tao Li
- Dr. Jinpeng Wei
- Dr. Zhenyu Yang
- Dr. Ming Zhao
Publications
- Lixi Wang, Jing Xu, Ming Zhao, Yicheng Tu, Jose Fortes, “Fuzzy Modeling based Resource Management for Virtualized Database Systems,” 19th Annual Meeting of the IEEE International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems (MASCOTS 2011), July 2011.
- Yangyang Wu, Ming Zhao, “Performance Modeling of Virtual Machine Live Migration,” 4th IEEE International Conference on Cloud Computing (CLOUD 2011), July 2011.
- Lixi Wang, Jing Xu, Ming Zhao, Jose Fortes, “Adaptive Virtual Resource Management with Fuzzy Model Predictive Control,” 6th International Workshop on Feedback Control Implementation and Design in Computing Systems and Networks (FeBID, co-held with ICAC’11), June 2011.
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Acknowledgement
| This material is based upon work supported by the Department of Homeland Security under grant 2010-ST-062-000039. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation. |