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A Simulation Execution Manager for ns-3: Encouraging reproducibility and simplifying statistical analysis of ns-3 simulations

Published: 25 November 2019 Publication History

Abstract

The typical workflow for ns-3 users consists of coming up with an experiment, translating that idea to simulation code, running multiple simulations, analyzing the outcomes, and finally plotting results. So far, the ns-3 project has not been providing tools to cover the steps from running simulations to obtaining plots: research teams typically develop their own custom solutions, and often need to learn new tools in order to reproduce results found in the literature. In this work we propose a framework that allows ns-3 users to go from their simulation script to plots in as few lines of code as possible, hiding tedious details about simulation running and result management, and leveraging Python's widely established statistical analysis tools to quickly perform simulations, analyze their outcomes, and plot results. The code and its documentation, which have been in part developed under the Google Summer of Code 2018 program, are publicly available at~\citesem, semdocs.

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Thomas R Henderson, Mathieu Lacage, George F Riley, Craig Dowell, and Joseph Kopena. 2008. Network simulations with the ns-3 simulator. SIGCOMM demonstration, Vol. 14, 14 (2008), 527.
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Davide Magrin. 2018a. A Simulation Execution Manager for ns-3 (Documentation). https://simulationexecutionmanager.readthedocs.io/en/develop/
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Davide Magrin. 2018b. A Simulation Execution Manager for ns-3 (Github Repository). https://github.com/signetlabdei/sem
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Christopher S. Main, L. Felipe Perrone, and Greg L. Schrock. 2014. Data visualization for network simulations. In Proceedings of the Winter Simulation Conference (WSC) .
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cover image ACM Conferences
MSWIM '19: Proceedings of the 22nd International ACM Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems
November 2019
340 pages
ISBN:9781450369046
DOI:10.1145/3345768
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 25 November 2019

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Author Tags

  1. ns-3
  2. result management
  3. simulation
  4. statistical analysis

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  • (2024)Full-Stack End-To-End Sub-THz Simulations at 140 GHz using NYUSIM Channel Model in ns-32024 IEEE Wireless Communications and Networking Conference (WCNC)10.1109/WCNC57260.2024.10570665(1-6)Online publication date: 21-Apr-2024
  • (2024)Programmable and Customized Intelligence for Traffic Steering in 5G Networks Using Open RAN ArchitecturesIEEE Transactions on Mobile Computing10.1109/TMC.2023.326664223:4(2882-2897)Online publication date: Apr-2024
  • (2024)A Hidden Parameter Study for Traffic-oriented LoRaWAN Deployment2024 International Wireless Communications and Mobile Computing (IWCMC)10.1109/IWCMC61514.2024.10592527(1376-1381)Online publication date: 27-May-2024
  • (2023)Improving the Efficiency of MIMO Simulations in ns-3Proceedings of the 2023 Workshop on ns-310.1145/3592149.3592167(1-9)Online publication date: 28-Jun-2023
  • (2023)Linux-like Socket Statistics Utility for ns-3Proceedings of the 2023 Workshop on ns-310.1145/3592149.3592164(121-126)Online publication date: 28-Jun-2023
  • (2023)ns-O-RAN: Simulating O-RAN 5G Systems in ns-3Proceedings of the 2023 Workshop on ns-310.1145/3592149.3592161(35-44)Online publication date: 28-Jun-2023
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  • (2022)A Multi-Gateway Behaviour Study for Traffic-Oriented LoRaWAN DeploymentFuture Internet10.3390/fi1411031214:11(312)Online publication date: 29-Oct-2022
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