Dataset Open Access

Wireless Link Quality Estimation on FlockLab - and Beyond

Romain Jacob; Reto Da Forno; Roman Trüb; Andreas Biri; Lothar Thiele

This repository contains wireless link quality estimation data for the FlockLab testbed [1,2]. The rationale and description of this dataset is described in a the following abstract (pdf is included in this repository -- see below).

Dataset: Wireless Link Quality Estimationon FlockLab – and Beyond
Romain Jacob, Reto Da Forno, Roman Trüb, Andreas Biri, Lothar Thiele
DATA '19 Proceedings of the 2nd Workshop on Data Acquisition To Analysis, 2019

Data collection scenario

The data collection scenario is simple. Each FlockLab node is assigned one dedicated time slot. In this slot, a node sends 100 packets, called strobes. All strobes have the same payload size and use a given radio frequency channel and transmit power. All other nodes listen for the strobes and log packet reception events (i.e., success or failed). 

The test scenario is ran every two hours on two different platforms: the TelosB [3] and DPP-cc430 [4] platforms. We used all 27 nodes currently available.

Current dataset status

  • 3 months of data with about 12 tests per day per platform
  • 1 month of data with about 4 tests per day per platform

Data collection firmware

We are happy to share the link quality data we collected for the FlockLab testbed, but we also wanted to make it easier for others to collect similar datasets for other wireless networks. To achieve this, we include in this repository the data collection firmware we design. The entire data collection scheduling and control is done entirely in software, in order to make the firmware usable in a large variety on wireless networks. We implemented our data collection software using Baloo [5], a flexible network stack design framework based on Synchronous Transmission. Baloo efficiently handles network time synchronization and offers a flexible interface to schedule communication rounds. The firmware source code is available in the Baloo repository [6].

A set of experiment parameters can be patched directly in the firmware, which let the user tune the data collection without having to recompile the source code. This improves usability and facilitates automation. An example patching script is included in this repository. Currently, the following parameters can be patched:

  • rf_channel,
  • payload,
  • host_id, and
  • rand_seed

Current supported platforms

  • TelosB [3]
  • DPP-cc430 [4]

Repository versions

  • v1.3.1
    Update abstract and notebook
  • v1.3.0
    Addition of October 2019 data.
    The frequency of tests has been reduced to 4 per day, executing at (approximately) 1:00, 7:00, 13:00, and 19:00.
    From October 28 onward, time shifted by one hour (2:00, 8:00, 14:00, 20:00).
  • v1.2.0
    Addition of September 2019 data.
    Many missing tests on the 12, 13, 19, and 20 of September (due to construction works in the building).
  • v1.1.4
    Update of the abstract to have hyperlinks to the plots. Corrected typos.
  • v1.1.0
    Initial version.
    Add the data collected in August 2019.
    Data collected was disturbed at the beginning of the month and resumed normally on the August 13. Data from previous days are incomplete.
  • v1.0.0
    Initial version.
    Contain collected data in July 2019, from the 10th to 30th of July.
    No data were collected on the 31st of July (technical issue).

List of files

  • yyyy-mm_raw_platform.zip
    Archive containing all FlockLab test result files (one .zip file per month and per platform).
  • yyyy-mm_preprocessed_all.zip
    Archive containing preprocessed csv files, one per month and per platform.
  • firmware.zip
    Archive containing the firmware for all supported platform.
  • firmware_patch.sh
    Example bash script illustrating the firmware patching.
  • parse_flocklab_results.ipynb [open in nbviewer]
    Jupyter notebook used to create the pre-process data files. Also includes some example of data visualization.
  • parse_flocklab_results.html
    HTML rendering of the notebook (static).
  • plots.zip
    Archive containing high resolution visualization of the dataset, generated by the parse_flocklab_results notebook, and presented in the abstract.
  • abstract.pdf
    A 3 page abstract presenting the dataset.
  • CRediT.pdf
    The list of contributions from the authors.

Dataset updates

We plan to carry-on collecting this data in the long-run (However, we will likely decrease the time resolution to free testing time up). The newly collected data will be added to this;repository periodically; we envision monthly updates.

References

[1] R. Lim, F. Ferrari, M. Zimmerling, C. Walser, P. Sommer, and J. Beutel, “FlockLab: A Testbed for Distributed, Synchronized Tracing and Profiling of Wireless Embedded Systems,” in Proceedings of the 12th International Conference on Information Processing in Sensor Networks, New York, NY, USA, 2013, pp. 153–166.

[2] “FlockLab,” GitLab. [Online]. Available: https://gitlab.ethz.ch/tec/public/flocklab/wikis/home. [Accessed: 24-Jul-2019].

[3] Advanticsys, “MTM-CM5000-MSP 802.15.4 TelosB mote Module.” [Online]. Available: https://www.advanticsys.com/shop/mtmcm5000msp-p-14.html. [Accessed: 21-Sep-2018].

[4] Texas Instruments, “CC430F6137 16-Bit Ultra-Low-Power MCU.” [Online]. Available: http://www.ti.com/product/CC430F6137. [Accessed: 21-Sep-2018].

[5] R. Jacob, J. Bächli, R. Da Forno, and L. Thiele, “Synchronous Transmissions Made Easy: Design Your Network Stack with Baloo,” in Proceedings of the 2019 International Conference on Embedded Wireless Systems and Networks, 2019.

[6] “Baloo,” Dec-2018. [Online]. Available: http://www.romainjacob.net/research/baloo/.

 

Files (1.3 GB)
Name Size
2019-07_preprocessed_all.zip
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13.7 MB Download
2019-07_raw_dpp-cc430.zip
md5:5065e81e6520e3eeda07aa465c407630
179.3 MB Download
2019-07_raw_sky.zip
md5:1faba6dc3432c905bc642468c98526e0
185.1 MB Download
2019-08_preprocessed_all.zip
md5:b1a9e3156f1be671f78cac448fb36f6f
16.6 MB Download
2019-08_raw_dpp-cc430.zip
md5:7dfee179f9ecc701cc497cd9f4c33edd
159.5 MB Download
2019-08_raw_sky.zip
md5:09585cf7209ce4f834fe9785031b6c77
178.6 MB Download
2019-09_preprocessed_all.zip
md5:fd838457ebcec2a6cd362fbe3bfec869
19.5 MB Download
2019-09_raw_dpp-cc430.zip
md5:893dce5196eefdd7c687868e5db1710b
195.7 MB Download
2019-09_raw_sky.zip
md5:1e00c07caff7f9eab8bd3e4c2e4de54a
212.4 MB Download
2019-10_preprocessed_all.zip
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4.3 MB Download
2019-10_raw_dpp-cc430.zip
md5:5a67f1f37340c5411066540513199900
89.5 MB Download
2019-10_raw_sky.zip
md5:0a1a4a40d7a96c2afab0109ed5553ce0
89.7 MB Download
abstract.pdf
md5:69d0f6423fcf8fb4e0e517545057685a
491.1 kB Download
CRediT.pdf
md5:e12b7c82f855251981ac48de36445abc
69.2 kB Download
firmware.zip
md5:1bd4fb4e2f2c4325c4ed7eccc8c9f4cf
154.5 kB Download
firmware_patch.zip
md5:885017fb716f66b6b624c0eecf627f88
3.4 kB Download
parse_flocklab_results.ipynb
md5:87551affdc05eaba98473bc3f8906a95
3.5 MB Download
plots.zip
md5:c0b0811f5ea62d96050621dee9f6eeac
84.5 kB Download
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