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Fault Tolerant Grid Workflow in Water Threat Management Master’s project / thesis seminar

Young Suk Moon Chair: Prof. Gregor von Laszewski Reader: Observer:. Fault Tolerant Grid Workflow in Water Threat Management Master’s project / thesis seminar. Outline. Brief summary of Water Threat Management Goal of the project

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Fault Tolerant Grid Workflow in Water Threat Management Master’s project / thesis seminar

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  1. Young Suk Moon Chair: Prof. Gregor von Laszewski Reader: Observer: Fault Tolerant Grid Workflowin Water Threat ManagementMaster’s project / thesis seminar

  2. Outline • Brief summary of Water Threat Management • Goal of the project • Background for my topic • Dynamic job scheduling • Fault tolerant grid systems • My ideas

  3. Water Threat Management project • Analyzing contamination of water in urban water distribution systems find the optimal solution find the contaminant source Simulation Engine (MPI)‏ Middle Ware Sensor Data Optimization Engine EPANET EPANET EPANET EPANET Grid Resources

  4. Goal of the project • Problems of the current WTM system (MPI)‏ • Not fault tolerant • All computing should restart from the beginning in case of node failure • Decision • Change MPI systems to loosely coupled systems

  5. Problems to solve • Run-time job scheduling • Fault tolerance

  6. Background: Dynamic resource selection Machines Job Queue Select machine Jobs Performance DB

  7. Background: Fault tolerance in grid • Replication • Run the same job in multiple nodes • Need more resources • Checkpoint-restart • Checkpoint server • Slow due to checkpoint overhead

  8. My ideas: Multiple-enqueue and Discard queue A Global Queue Machine A queue B Jobs 5 4 3 2 1 Machine B queue C Machine C

  9. My ideas: Multiple-enqueue and Discard queue A 3 3 3 2 2 2 1 1 1 Global Queue Machine A queue B Jobs 10 9 8 7 6 4 3 3 2 2 3 1 1 2 Machine B queue C 3 3 5 2 4 2 1 3 1 Machine C

  10. Issues • How many duplicated jobs to enqueue • How to allocate which jobs to which machines • How to divide jobs or input data • How to cluster nodes

  11. Evaluation • Comparison based on the different settings

  12. References • G. von Laszewski, K. Mahinthakumar, R. Ranjithan, D. Brill, J. Uber, K. Harrison, S. Sreepathi, and E. Zechman, “An Adaptive Cyberinfrastructure for Threat Management in Urban Water Distribution Systems,” in Proceedings of ICCS 2006, vol. 3993, 2006, pp. 401–. • S. Sreepathi, “CYBERINFRASTRUCTURE FOR CONTAMINATION SOURCE CHARACTERIZATION IN WATER DISTRUBUTION SYSTEMS,” Master’s thesis, North Carolina State University, 2006 • G. von Laszewski, “A Loosely Coupled Metacomputer: Cooperating Job Submissions Across Multiple Supercomputing Sites,” Concurrency, Experience, and Practice, vol. 11, no. 5, pp. 933–948, Dec. 1999 • L. Ramakrishnam and D. A. Reed, “Performability modeling for scheduling and fault tolerance strategies for scientific workflows,” in Proceedings of the 17th international symposium on High performance distributed computing, 2008. • S. Ayyub and D. Abramson, “GridRod - A Dynamic Runtime Scheduler for Grid Workflows,” in Proceedings of the 21st annual international conference on Supercomputing, 2007.

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