survey

Co-Simulation: A Survey

Authors:

Cláudio Gomes,

Peter Gorm Larsen, and

Hans VangheluweAuthors Info & Claims

ACM Computing Surveys (CSUR), Volume 51, Issue 3

Article No.: 49, Pages 1 - 33

https://doi.org/10.1145/3179993

Published: 23 May 2018 Publication History

Abstract

Modeling and simulation techniques are today extensively used both in industry and science. Parts of larger systems are, however, typically modeled and simulated by different techniques, tools, and algorithms. In addition, experts from different disciplines use various modeling and simulation techniques. Both these facts make it difficult to study coupled heterogeneous systems.

Co-simulation is an emerging enabling technique, where global simulation of a coupled system can be achieved by composing the simulations of its parts. Due to its potential and interdisciplinary nature, co-simulation is being studied in different disciplines but with limited sharing of findings.

In this survey, we study and survey the state-of-the-art techniques for co-simulation, with the goal of enhancing future research and highlighting the main challenges.

To study this broad topic, we start by focusing on discrete-event-based co-simulation, followed by continuous-time-based co-simulation. Finally, we explore the interactions between these two paradigms, in hybrid co-simulation.

To survey the current techniques, tools, and research challenges, we systematically classify recently published research literature on co-simulation, and summarize it into a taxonomy. As a result, we identify the need for finding generic approaches for modular, stable, and accurate coupling of simulation units, as well as expressing the adaptations required to ensure that the coupling is correct.

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Index Terms

Co-Simulation: A Survey
1. Computing methodologies
  1. Modeling and simulation

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cover image ACM Computing Surveys

ACM Computing Surveys Volume 51, Issue 3

May 2019

796 pages

ISSN:0360-0300

EISSN:1557-7341

DOI:10.1145/3212709

Editor:
Sartaj Sahni
Department of Computer and Information Science and Engineering / University of Florida / Gainesville, FL 32611

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Publication History

Published: 23 May 2018

Accepted: 01 January 2018

Revised: 01 December 2017

Received: 01 February 2017

Published in CSUR Volume 51, Issue 3

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