NDLI: Using Distributed Analytics to Enable Real-Time Exploration of Discrete Event Simulations

Content Provider	IEEE Xplore Digital Library
Author	Malensek, Matthew Budgaga, Walid Pallickara, Sangmi Harvey, Neil Breidt, F. Jay Pallickara, Shrideep
Copyright Year	2014
Abstract	Discrete event simulations (DES) provide a powerful means for modeling complex systems and analyzing their behavior. DES capture all possible interactions between the entities they manage, which makes them highly expressive but also compute-intensive. These computational requirements often impose limitations on the breadth and/or depth of research that can be conducted with a discrete event simulation. This work describes our approach for leveraging the vast quantity of computing and storage resources available in both private organizations and public clouds to enable real-time exploration of a discrete event simulation. Rather than considering the execution speed of a single simulation run, we autonomously generate novel scenario variants to explore an entire subset of the simulation parameter space. These workloads are orchestrated in a distributed fashion across a wide range of commodity hardware. The resulting outputs are analyzed to produce models that accurately forecast simulation outcomes in real time, providing interactive feedback and bolstering research possibilities.
Starting Page	49
Ending Page	58
File Size	401134
Page Count	10
File Format	PDF
ISBN	9781479978816
DOI	10.1109/UCC.2014.13
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-12-08
Publisher Place	United Kingdom
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Discrete Event Simulation Computational modeling Distributed Execution Probability density function Predictive models Hypercubes Real-time systems Discrete event simulation Cloud Infrastructure Latin Hypercube Sampling Diseases
Content Type	Text
Resource Type	Article

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