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  4. Performance Evaluation of Automated Guided Vehicles: Use Case of using OMNeT++ in a Master's Thesis
 
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Performance Evaluation of Automated Guided Vehicles: Use Case of using OMNeT++ in a Master's Thesis

Publikationstyp
Conference Paper
Date Issued
2019
Sprache
English
Author(s)
Hariharanagarajan, Kaushik  
Krüger, Leo  orcid-logo
Kuladinithi, Koojana  orcid-logo
Timm-Giel, Andreas  orcid-logo
Institut
Kommunikationsnetze E-4  
TORE-URI
http://hdl.handle.net/11420/4528
First published in
EPiC series in computing  
Number in series
66
Volume
66
Start Page
11
End Page
23
Citation
Meyo Zongo, Antonio Virdis, Vladimir Vesely, Zeynep Vatandas, Asanga Udugama, Koojana Kuladinithi, Michael Kirsche and Anna Förster (editors). Proceedings of 6th International OMNeT++ Community Summit 2019, EPiC series in computing 66: 11-23 (2019)
Contribution to Conference
6th International OMNeT++ Community Summit 2019  
Publisher DOI
10.29007/bfmq
Scopus ID
2-s2.0-85080068322
Publisher
EasyChair
OMNeT++ as a discrete event simulator is widely used in combination with the INET framework to simulate communication networks. For students, the limited time frame designated for their master’s thesis is usually a challenge. In particular, because not only an implementation but a scientific contribution is expected as well. Within this paper we present an approach on how OMNeT++ can be used to solve the research question given in the context of a thesis. The exemplary application scenario under consideration here is based on Automated guided vehicles (AGV) which use a WLAN network to exchange information about new obstacles and their localization as such with a central server. As the performance indicators of communication networks are not yet considered while planning such setups, the effect of the network on the operation of the AGVs has to be evaluated. Especially in scenarios with a large number of AGVs the scalability of the WLAN is of interest. We show how the simulation model is parametrized based on a field analysis. With the aid of the experimental data, the different types of traffic are distinguished and modelled according to probability distributions. Based on the scenario under consideration and the envisioned large scale setups, a simulation model is implemented. In the evaluation we present exemplary results. We conclude with an explanation of the grading scheme of master’s theses to highlight how the scientific approach presented is taken into account here.
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