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  4. TAWNS - A Terrestrial Acoustic and Wireless Network Simulation Framework
 
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2023
Conference Paper
Title

TAWNS - A Terrestrial Acoustic and Wireless Network Simulation Framework

Abstract
Wireless Sensor Networks that address audio-related applications have been researched for over a decade. But reproducibility and customizability are a challenge when focusing on research questions in outdoor environments (e.g., localization of wildlife species). It usually involved the design of customized prototypes and time-consuming and often error-prone deployments to generate a ground truth. In this paper, we propose TAWNS, an Open Source model framework for Omnet++/INET which supports researchers conducting simulations on wireless acoustic sensor networks - either as the main focus of study or as a component. It inherits all the networking and wireless communication elements supported by the library INET and provides a novel, easy-to-use spatial audio simulator for 3-D sound environments. For the latter, we adapted and extended the library Scaper by adding a customized model for attenuating and delaying the acoustic signals. Our model parameters are derived from multiple measurements with different hardware. We share them in this paper, serving as a basis for other researchers. To give an impression of the hardware requirements, we also evaluate the system resources of our simulator.
Author(s)
Brüggemann, Leonhard
Schütz, Bertram
Fraunhofer-Institut für Kommunikation, Informationsverarbeitung und Ergonomie FKIE  
Aschenbruck, Nils
Mainwork
Performance Evaluation Methodologies and Tools. 15th EAI International Conference, VALUETOOLS 2022. Proceedings  
Conference
International Conference on Performance Evaluation Methodologies and Tools 2022  
DOI
10.1007/978-3-031-31234-2_18
Language
English
Fraunhofer-Institut für Kommunikation, Informationsverarbeitung und Ergonomie FKIE  
Keyword(s)
  • bioacoustic research

  • INET

  • Omnet++

  • simulator

  • spatial sound generation

  • TAWNS

  • WASN

  • wireless acoustic sensor networks

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