Applied Sciences (Dec 2023)

Speed Optimization in DEVS-Based Simulations: A Memoization Approach

  • Bo Seung Kwon,
  • Young Shin Han,
  • Jong Sik Lee

DOI
https://doi.org/10.3390/app132312958
Journal volume & issue
Vol. 13, no. 23
p. 12958

Abstract

Read online

The DEVS model, designed for general discrete event simulation, explores the event status and time advance of all DEVS atomic models deployed at the time of the simulation, and then performs the scheduled simulation step. Each simulation step is accompanied by a re-exploration the event status and time advance, which is needed for maintaining the casual order of the entire model. It is time consuming to simulate a large-scale DEVS model. In a similar vein, attempts to perform an HDL simulation in a DEVS space increase simulation costs by incurring repeated search costs for model transitions. In this study, we performed a statistical analysis of engine behavior to improve simulation speed and we proposed a DP-based memoization technique for the coupled model. Through our method, we can expect significant performance improvements that range statistically from 7.4 to 11.7 times.

Keywords