Page 61 - profile2014.indd

副研究員
王建民 Chien-Min Wang

Associate Research Fellow
Ph.D., Electrical Engineering, National Taiwan University
Tel: +886-2-2788-3799 ext. 1703 Fax: +886-2-2782-4814
Email: cmwang@iis.sinica.edu.tw
http://www.iis.sinica.edu.tw/pages/cmwang

Research Description ● Associate Research Fellow, IIS,
Academia Sinica (1996 - )
My research interest is in the area of parallel and distributed computing, with an emphasis ● Assistant Research Fellow, IIS,
on software support and optimization techniques for data-intensive applications. We have Academia Sinica (1991 - 1995)
addressed replica and server placement problems in various distributed environments to ● Ph.D., EE, National Taiwan Univer-
improve reliability and performance of the systems. We have studied replication transition sity (1991)

problems so that the replica placement can adapt to user preference and system con gu- ● B.S., EE, National Taiwan Univer-

ration. With multiple servers in the systems, we have proposed e cient algorithms to im- sity (1987)
prove the aggregate bandwidth and reliability of data transfers. We have also investigated
resource management problems and proposed bidding-based mechanisms for resource ● Best paper award at the 2006
International Conference on Grid
selection in distributed systems. and Pervasive Computing.
Recently, we have focused on storage and processing of streaming data in Clouds and vir-
tualization for multi-cores. Cloud computing is a new and promising paradigm for enabling
ubiquitous, convenient, on-demand network access to a shared pool of con gurable com-

puting resources that can be rapidly provisioned and released. As more and more streaming data applications are moved to Clouds,

e cient parallel frameworks and distributed le systems are the key to meeting the scalability and performance requirements entailed
in such streaming data applications. We shall aim at the provision of QoS in distributed le systems with the goals of meeting the

bandwidth/latency requirement of each access and improving the overall utilization of storage resources. At the same time, we shall
extend the general applicability of MapReduce and develop methodology and software tools that are able to process streaming data

e ciently. Virtualization is a very important technology for multi-cores and Clouds. It allows applications running on such systems to be

agnostic about the underlying platforms. Our research e ort focuses on the core technologies, such as dynamic compilation techniques

for binary translation, binary optimization targeting multi-core systems, and e cient runtime support for system-mode virtualization.

Publications
1. Chien-Min Wang, Chun-Chen Hsu, Pangfeng Liu, Hsi-Min Wu, Ding-Yong Hong, Pen-Chung Yew, and Wei-Chung Hsu,
Chen, and Jan-Jan Wu, “Optimizing Server Placement in Hier- “LnQ: Building High Performance Dynamic Binary Transla-
archical Grid Environments,” The Journal of Supercomputing, tors with Existing Compiler Backends,” Proceedings of the
th
pp. 267-282, Vo. 42, No. 3, December 2007. 40 International Conference on Parallel Processing, pp. 226-
234, Taipei, Taiwan, Sep. 2011.
2. Chun-Chen Hsu, Chien-Min Wang, and Pangfeng Liu, “Opti-
mal Replication Transition Strategy in Distributed Hierarchi- 7. Jan-Jan Wu, Shu-Fan Shih, Hsiangkai Wang, Pangfeng Liu,
nd
cal Systems,” Proceedings of the 22 IEEE International Par- and Chien-Min Wang, “QoS-aware Replica Placement for
allel and Distributed Processing Symposium, Miami, Florida, Grid Computing,” Concurrency and Computation: Practice
USA, April 2008. and Experience, pp. 193-213, Vol. 24, No. 3, March 2012.
3. Jan-Jan Wu, Yi-Fang Lin, Da-Wei Wang, and Chien-Min 8. Chien-Min Wang, Tse-Chen Yeh, and Guo-Fu Tseng, “Provi-
Wang, “Optimizing Server Placement for Parallel I/O in sion of Storage QoS in Distributed File Systems for Clouds,”
Switch-based Clusters,” Journal of Parallel and Distributed Proceedings of the 41 International Conference on Parallel
th
Computing, Vol. 69, No. 3, pp. 266-281, March 2009. Processing, pp. 189-198, Pittsburgh, USA, Sep. 2012.
4. Chien-Min Wang, Hsi-Min Chen, Chun-Chen Hsu, and Jona- 9. Ding-Yong Hong, Jan-Jan Wu, Pen-Chung Yew, Wei-Chung
than Lee, “Dynamic Resource Selection Heuristics for a Non- Hsu, Chun-Chen Hsu, Pangfeng Liu, Chien-Min Wang, and

reserved Bidding-based Grid Environment,” Future Genera- Yeh-Ching Chung, “Efficient and Retargetable Dynamic Bi-
tion Computer Systems, Vol. 26, No. 2, pp. 183-197, 2010. nary Translation on Multicores,” IEEE Transactions on Par-
allel and Distributed Systems, Vol. 25, No. 3, pp. 622-632,
5. Chien-Ming Wang, Chi-Chang Huang, and Huan-Ming Liang, February 2014.
“ASDF: An Autonomous and Scalable Distributed File Sys-
tem,” Proceedings of the 11 IEEE/ACM International Sym- 10. Hsiang-Huang Wu, Tse-Chen Yeh, and Chien-Min Wang,
th
posium on Cluster, Cloud and Grid Computing, pp. 485-493, “Multiple Two-Phase Data Processing with MapReduce,” to
Los Angeles, USA, May 2011. appear in the 2014 IEEE International Conference on Cloud
Computing, Alaska, USA, June 2014.
6. Chun-Chen Hsu, Pangfeng Liu, Chien-Min Wang, Jan-Jan

61