An Adaptive Cyberinfrastructure for Threat Management in Urban Water Distribution Systems

Kumar Mahinthakumar1, Gregor von Laszewski2, Ranji Ranjithan1, Downey Brill1, Jim Uber3, Ken Harrison4, Sarat Sreepathi1, and Emily Zechman1

1 North Carolina State University, Raleigh, NC, USA
gmkumar@ncsu.edu
ranji@ncsu.edu
brill@ncsu.edu
sarat_s@ncsu.edu
emzechma@ncsu.edu

2 University of Chicago, Chicago, IL, USA
gregor@mcs.anl.gov

3 University of Cincinnati, Cincinnati, OH, USA
jim.uber@uc.edu

4 University of South Carolina, Columbia, SC, USA
harriskw@engr.sc.edu

Abstract. Threat management in drinking water distribution systems involves real-time characterization of any contaminant source and plume, design of control strategies, and design of incremental data sampling schedules. This requires dynamic integration of time-varying measurements along with analytical modules that include simulation models, adaptive sampling procedures, and optimization methods. These modules are compute-intensive, requiring multi-level parallel processing via computer clusters. Since real-time responses are critical, the computational needs must also be adaptively matched with available resources. This requires a software system to facilitate this integration via a high-performance computing architecture such that the measurement system, the analytical modules and the computing resources can mutually adapt and steer each other. This paper describes the development of such an adaptive cyberinfrastructure system facilitated by a dynamic workflow design.

LNCS 3993, pp. 401-408.

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