Resense: Transparent Record and Replay of Sensor Data in the Internet of Things

Dimitrios Giouroukis 1 Julius Hülsmann 1 Janis von Bleichert 1 Morgan Geldenhuys 1 Tim Stullich 1 Felipe Oliveira Gutierrez 1 Jonas Traub 1 Kaustubh Beedkar 1 Volker Markl 1
1 TUB - Technische Universität Berlin
Abstract : As the scientific interest in the Internet of Things (IoT) continues to grow, emulating IoT infrastructure involving a large number of heterogeneous sensors plays a crucial role. Existing research on emulating sensors is often tailored to specific hardware and/or software, which makes it difficult to reproduce and extend. In this paper we show how to emulate different kinds of sensors in a unified way that makes the downstream application agnostic as to whether the sensor data is acquired from real sensors or is read from memory using emulated sensors. We propose the Resense framework that allows for replaying sensor data using emulated sensors and provides an easy-to-use software for setting up and executing IoT experiments involving a large number of heterogeneous sensors. We demonstrate various aspects of Resense in the context of a sports analytics application using real-world sensor data and a set of Raspberry Pis.
Document type :
Conference papers
Complete list of metadatas

Cited literature [15 references]  Display  Hide  Download
https://hal.inria.fr/hal-02056767
Contributor : Guillaume Pierre <>
Submitted on : Monday, March 4, 2019 - 5:59:26 PM
Last modification on : Monday, April 1, 2019 - 11:14:04 AM
Long-term archiving on: Wednesday, June 5, 2019 - 4:32:46 PM

File

i2c-main.pdf
Files produced by the author(s)

Identifiers

  • HAL Id : hal-02056767, version 1

Collections

Citation

Dimitrios Giouroukis, Julius Hülsmann, Janis von Bleichert, Morgan Geldenhuys, Tim Stullich, et al.. Resense: Transparent Record and Replay of Sensor Data in the Internet of Things. 22nd International Conference on Extending Database Technology (EDBT), Mar 2019, Lisbon, Portugal. ⟨hal-02056767⟩

Export

BibTeX TEI DC DCterms EndNote

Share

Metrics

Record views

172

Files downloads

175

 

 

Contact

archive-ouverte@inria.fr