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Issue No.01 - Jan.-Feb. (2014 vol.16)
pp: 8-17
Lizhe Wang , China University of Geosciences
Dan Chen , China University of Geosciences
Wangyang Liu , China University of Geosciences
Yan Ma , Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences
Yanhui Wu , Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences
Ze Deng , China University of Geosciences
ABSTRACT
Contaminant source characterization (CSC) in a water distribution system (WDS) exhibits a computationally intensive problem. Traditional solutions to the CSC problem can't fulfill the CSC's quality-of-service (QoS) requirements. We present a parallel solution using the MapReduce paradigm in the cloud that can deliver a high-performance, fault-tolerant, and flexible solution.
INDEX TERMS
Computational modeling, Genetic algorithms, Optimization, Contamination, Cloud computing, Encoding,scientific computing, cloud computing, MapReduce, Hadoop, cyberinfrastructure
CITATION
Lizhe Wang, Dan Chen, Wangyang Liu, Yan Ma, Yanhui Wu, Ze Deng, "DDDAS-Based Parallel Simulation of Threat Management for Urban Water Distribution Systems", Computing in Science & Engineering, vol.16, no. 1, pp. 8-17, Jan.-Feb. 2014, doi:10.1109/MCSE.2012.89
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