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16.02.2021
Martin Pagel

The Paper “Automatic Tuning of Read-Time Tolerances for Optimized On-Demand Data-Streaming from Sensor Nodes” Accepted for Publication at EDBT 2021

The research paper “Automatic Tuning of Read-Time Tolerances for Optimized On-Demand Data-Streaming from Sensor Nodes,” authored by Julius Hülsmann, Chiao-Yun Li, Jonas Traub and Volker Markl will be presented at the 24th International Conference on Extending Database Technology (EDBT 2021), the week of March 23-26, 2021.

Abstract :
The Internet of Things provides applications with data streams from billions of sensor devices in real-time. Usually, sensor devices serve multiple queries simultaneously despite having limited computational capabilities. This paper presents a solution for reducing the number of data reads and transmissions by increasing the potential for sharing reads among concurrent streaming queries. Existing read-scheduling techniques on sensor nodes dynamically adjust the data-acquisition rate depending on the data’s variability. However, they leave the definition of read-time tolerances to the user. Such read-time tolerances are crucial for sharing reads among queries. We extend previous work by presenting a generally-applicable algorithm that defines read-time tolerances and adapts them on-the-fly depending on observed data characteristics. We evaluate our solution on real-world data and show that it reduces the sensing error by up to 60% compared to existing approaches with the same number of data reads. Respectively, our technique reduces the number of data reads to achieve the same sensing error as existing techniques. To the best of our knowledge, we are the first to automatically set and tune read-time tolerances to reduce sensor readings and data transmissions on sensor nodes.

To download a preprint of the “Automatic Tuning of Read-Time Tolerances for Optimized On-Demand Data-Streaming from Sensor Nodes” paper visit: https://bit.ly/3an3kAx.

For more information about the EDBT 2021 conference visit: https://edbticdt2021.cs.ucy.ac.cy/.