A unified cloud-enabled discrete event parallel and distributed simulation architecture



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Risco Martín, José Luis and Henares Vilaboa, Kevin and Mittal, Saurabh and Almendras Aruzamen, Luis Fernando and Olcoz Herrero, Katzalin (2022) A unified cloud-enabled discrete event parallel and distributed simulation architecture. Simulation modelling practice and theory, 118 . ISSN 1569-190X

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Official URL: http://dx.doi.org/10.1016/j.simpat.2022.102539


Cloud infrastructure provides rapid resource provision for on-demand computational require-ments. Cloud simulation environments today are largely employed to model and simulate complex systems for remote accessibility and variable capacity requirements. In this regard, scalability issues in Modeling and Simulation (M & S) computational requirements can be tackled through the elasticity of on-demand Cloud deployment. However, implementing a high performance cloud M & S framework following these elastic principles is not a trivial task as parallelizing and distributing existing architectures is challenging. Indeed, both the parallel and distributed M & S developments have evolved following separate ways. Parallel solutions has always been focused on ad-hoc solutions, while distributed approaches, on the other hand, have led to the definition of standard distributed frameworks like the High Level Architecture (HLA) or influenced the use of distributed technologies like the Message Passing Interface (MPI). Only a few developments have been able to evolve with the current resilience of computing hardware resources deployment, largely focused on the implementation of Simulation as a Service (SaaS), albeit independently of the parallel ad-hoc methods branch. In this paper, we present a unified parallel and distributed M & S architecture with enough flexibility to deploy parallel and distributed simulations in the Cloud with a low effort, without modifying the underlying model source code, and reaching important speedups against the sequential simulation, especially in the parallel implementation. Our framework is based on the Discrete Event System Specification (DEVS) formalism. The performance of the parallel and distributed framework is tested using the xDEVS M & S tool, Application Programming Interface (API) and the DEVStone benchmark with up to eight computing nodes, obtaining maximum speedups of 15.95x and 1.84x, respectively.

Item Type:Article
Additional Information:

©2022 Elsevier
This project has been partially supported by the Education and Research Council of the Community of Madrid (Spain), under research grant S2018/TCS- 4423, and by the Google Cloud Research Credits program with the award GCP19980904.

Uncontrolled Keywords:Framework; Discrete-event simulation; Parallel simulation; Distributed simulation; High performance computing; Cloud computing
Subjects:Sciences > Computer science > Artificial intelligence
ID Code:72754
Deposited On:15 Jun 2022 16:29
Last Modified:16 Jun 2022 07:04

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