TY - JOUR
T1 - Large-scale simulations manager tool for OmNet++
T2 - Expediting simulations and post-processing analysis
AU - Barbecho Bautista, Pablo Andrés
AU - Urquiza-Aguiar, Luis Felipe
AU - Cárdenas, Leticia Lemus
AU - Igartua, Mónica Aguilar
N1 - Publisher Copyright:
© 2020 Institute of Electrical and Electronics Engineers Inc.. All rights reserved.
PY - 2020
Y1 - 2020
N2 - Usually, simulations are the first approach to evaluate wireless and mobile networks due to the difficulties involved in deploying real test scenarios. Working with simulations, testing, and validating the target network model often requires a large number of simulation runs. Consequently, there are a significant amount of outcomes to be analyzed to finally plot results. One of the most extensively used simulators for wireless and mobile networks is OMNeT++. This simulation environment provides useful tools to automate the execution of simulation campaigns, yet single-scenario simulations are also supported where the assignation of resources (i.e., CPUs) has to be declared manually. However, conducting a large number of simulations is still cumbersome and can be improved to make it easier, faster, and more comfortable to analyze. In this work, we propose a large-scale simulations framework called simulations manager for OMNeT++ (SMO). SMO allows OMNeT++ users to quickly and easily execute large-scale network simulations, hiding the tedious process of conducting big simulation campaigns. Our framework automates simulations executions, resources assignment, and post-simulation data analysis through the use of Python’s wide established statistical analysis tools. Besides, our tool is flexible and easy to adapt to many different network scenarios. Our framework is accompanied by a command-line environment allowing a fast and easy manipulation that allows users to significantly reduce the total processing time to carry out large sets of simulations about 25% of the original time. Our code and its documentation are publicly available at GitHub and on our website.
AB - Usually, simulations are the first approach to evaluate wireless and mobile networks due to the difficulties involved in deploying real test scenarios. Working with simulations, testing, and validating the target network model often requires a large number of simulation runs. Consequently, there are a significant amount of outcomes to be analyzed to finally plot results. One of the most extensively used simulators for wireless and mobile networks is OMNeT++. This simulation environment provides useful tools to automate the execution of simulation campaigns, yet single-scenario simulations are also supported where the assignation of resources (i.e., CPUs) has to be declared manually. However, conducting a large number of simulations is still cumbersome and can be improved to make it easier, faster, and more comfortable to analyze. In this work, we propose a large-scale simulations framework called simulations manager for OMNeT++ (SMO). SMO allows OMNeT++ users to quickly and easily execute large-scale network simulations, hiding the tedious process of conducting big simulation campaigns. Our framework automates simulations executions, resources assignment, and post-simulation data analysis through the use of Python’s wide established statistical analysis tools. Besides, our tool is flexible and easy to adapt to many different network scenarios. Our framework is accompanied by a command-line environment allowing a fast and easy manipulation that allows users to significantly reduce the total processing time to carry out large sets of simulations about 25% of the original time. Our code and its documentation are publicly available at GitHub and on our website.
KW - Large-scale simulations
KW - OMNeT++
KW - Results post-processing
UR - https://www.scopus.com/pages/publications/85102757813
U2 - 10.1109/ACCESS.2020.3020745
DO - 10.1109/ACCESS.2020.3020745
M3 - Artículo
AN - SCOPUS:85102757813
SN - 2169-3536
VL - 8
SP - 159291
EP - 159306
JO - IEEE Access
JF - IEEE Access
ER -