MoDD: A Model-Driven Framework For Data Collection In Drone-Based Systems - Université de Bretagne Occidentale
Conference Papers Year : 2024

MoDD: A Model-Driven Framework For Data Collection In Drone-Based Systems

Abstract

Nowadays, Cyber-Physical Systems (CPS), particularly drones, play a pivotal role in environmental research. Scientists depend on these platforms to monitor various sensor data and ensure comprehensive data archiving. However, despite their advantages, researchers encounter several challenges, including communication limitations and the complexity of setting up systems tailored to their needs. To address these issues, we propose MoDD, a model-driven data collection framework based on a customized publish/subscribe model. MoDD simplifies the development and configuration of data collection systems. It offers scientists a solution that meets their specific needs, allowing them to focus on high-level requirements while the framework manages the underlying complexities. We demonstrate the effectiveness of MoDD through practical evaluations on an actual Unmanned Surface Vehicle. Additionally, results show a 79% reduction in throughput (drone to base station link) compared to existing publish/subscribe systems.
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Dates and versions

hal-04720939 , version 1 (04-10-2024)
hal-04720939 , version 2 (23-10-2024)

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Manele Ait Habouche, Mickaël Kerboeuf, Goulven Guillou, Jean-Philippe Babau. MoDD: A Model-Driven Framework For Data Collection In Drone-Based Systems. 50th Euromicro Conference Series on Software Engineering and Advanced Applications (SEAA 2024), Aug 2024, Paris, France. ⟨10.1109/SEAA64295.2024.00013⟩. ⟨hal-04720939v1⟩
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