Published: Oct 21, 2009 8:27:00 AM
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Xiao Qin, faculty member in Auburn University's Department of Computer Science and Software Engineering (CSSE) was recently chosen as lead investigator for a $500,000 National Science Foundation (NSF) grant for a project entitled, "Collaborative Research: FastStor: Data-Mining-Based Multilayer Prefetching for Hybrid Storage Systems." Co-principal investigators for the project include faculty members Ziliang Zong of the South Dakota School of Mines and Technology and Mias Nijim of the University of Southern Mississippi. Also working on the project as co-investigators are Auburn faculty members Wei-Shinn Ku and Wei-Kuan Yu of CSSE.
The three-year project is designed to build data-mining-based multilayer prefetching techniques to improve the performance of data centers with hybrid storage systems. The technology results in data being loaded from disks to main memory before it is accessed from the disks, thus improving performance and reliability of hybrid storage systems with solid state disks (SSDs), hard disks (HDDs) and tapes. The main goals of the research are to design data-mining algorithms for multilayer prefetching, develop a predictive parallel prefetching mechanism for SSD-based storage systems, implement parallel data transfer among SSDs, HHDs and tapes, develop meta-data management schemes and implement a simulation framework named FastStor-SIM.
Qin joined the Auburn Engineering faculty in 2007. He holds bachelor's and master's degrees in computer science from Huazhong University of Science and Technology in China, and received his doctorate in computer science from the University of Nebraska-Lincoln in 2004. His research interests include reliability modeling, performance evaluation, fault tolerance, storage systems and real-time computing, as well as parallel and distributed systems.
Contributed by Cassity Hughes