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Parallel Simulation of Threat Management for Urban Water Distribution Systems with MapReduce in Clouds
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ISSN: 1521-9615
| ASCII Text | x | ||
| Lizhe Wang, Dan Chen, wangyang liu, Yan Ma, Yanhui Wu, Ze Deng, "Parallel Simulation of Threat Management for Urban Water Distribution Systems with MapReduce in Clouds," Computing in Science and Engineering, vol. 99, no. 1, pp. 1-1, , 5555. | |||
| BibTex | x | ||
| @article{ 10.1109/MCSE.2012.89, author = {Lizhe Wang and Dan Chen and wangyang liu and Yan Ma and Yanhui Wu and Ze Deng}, title = {Parallel Simulation of Threat Management for Urban Water Distribution Systems with MapReduce in Clouds}, journal ={Computing in Science and Engineering}, volume = {99}, number = {1}, issn = {1521-9615}, year = {5555}, pages = {1-1}, doi = {http://doi.ieeecomputersociety.org/10.1109/MCSE.2012.89}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, } | |||
| RefWorks Procite/RefMan/Endnote | x | ||
| TY - MGZN JO - Computing in Science and Engineering TI - Parallel Simulation of Threat Management for Urban Water Distribution Systems with MapReduce in Clouds IS - 1 SN - 1521-9615 SP1 EP1 EPD - 1-1 A1 - Lizhe Wang, A1 - Dan Chen, A1 - wangyang liu, A1 - Yan Ma, A1 - Yanhui Wu, A1 - Ze Deng, PY - 5555 VL - 99 JA - Computing in Science and Engineering ER - | |||
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/MCSE.2012.89
The Contaminant Source Characterization (CSC) problem in a Water Distributed System (WDS) exhibits a compute-intensive challenge that requires highly reliable and high performance computing resources in order to achieve near real-time processing. Traditional solution to the CSC problem with MPI via Grid/cluster computing cannot fulfill CSC’s QoS requirements, such as, reliability, scalability and flexibility. To address the aforementioned research issues, we have developed a parallel solution to the CSC problem using MapReduce in Clouds, which mainly includes 1) parallelization of the process of evaluating individuals in the Genetic Algorithm for CSC with MapReduce, and 2) developing an advanced cyberinfrastructure in an academic Cloud computing test bed (the FutureGrid test bed). We have carried out performance evaluation and discussion on our solution. Test results and performance evaluation show that parallel GA with MapReduce in a dynamic cyberinfrastructure can deliver a high performance, fault tolerance and flexible solution for the CSC problem.
Citation:
Lizhe Wang, Dan Chen, wangyang liu, Yan Ma, Yanhui Wu, Ze Deng, "Parallel Simulation of Threat Management for Urban Water Distribution Systems with MapReduce in Clouds," Computing in Science and Engineering, 30 July 2012. IEEE computer Society Digital Library. IEEE Computer Society, <http://doi.ieeecomputersociety.org/10.1109/MCSE.2012.89>
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