Simulation Outputs for the "DYNAMIC" Framework Study

This dataset contains simulation results that were used to produce the main figure in: LOJDA, J.; STRNADEL, J.; SMRŽ, P.; ŠIMEK, V. First Steps Towards Unified Low-Power IoT Design: The “DYNAMIC” Framework. 2024 IEEE East-West Design and Test Symposium (EWDTS 2024) - Proceedings, Yerevan: Institute of Electrical and Electronics Engineers, 2024, pp. 1–6. ISBN 979-8-3315-1576-8. DOI: 10.5281/zenodo.16779333 1. Description The dataset contains outputs from a discrete-event simulation (Python/SimPy) of a low-power IoT temperature-monitoring device, modeled according to the parameters described in the referenced paper. The experiments investigate different power management strategies implemented within the proposed DYNAMIC framework, with and without Energy Harvesting (EH). The simulated device characteristics: Battery: Li-Ion, 1000 mAh, voltage range 3.4–4.2 V Communication module: Single transmission cost ~1.944 J (≈0.15 mAh at 3.6 V) Default reporting interval: Every 5 minutes EH model: 10 mA charging for 4 hours/day (~40 mAh/day) Tested configurations: No Power Management (noPM) — baseline “Amount” Power Management Algorithm (amountPM) “Slope” Power Management Algorithm (slopePM)Each was tested with and without Energy Harvesting. Simulation length: 60 days (5,184,000 seconds) of operation. 2. File Contents Files contain battery charge in time for various setups: File name Description 1_noPM_noEH.csv No power management, no energy harvesting 2_noPM_withEH.csv No power management, with energy harvesting 3_amountPM_noEH.csv “Amount” algorithm, no energy harvesting 4_amountPM_withEH.csv “Amount” algorithm, with energy harvesting 5_slopePM_noEH.csv “Slope” algorithm, no energy harvesting 6_slopePM_withEH.csv “Slope” algorithm, with energy harvesting charge_in_time.pdf Visualization of battery charge and user experience over time for all scenarios 3. CSV File Format Each .csv file contains comma-separated values with the following columns: Elapsed Time (s) — Seconds since the beginning of the experiment. Battery Charge (mAh) — Current battery state of charge. User Experience Deviation (minutes) If the device is operational, this is the difference in reporting latency compared to the default 5-minute interval (can be positive or negative). If the device is offline due to battery depletion, the value represents the difference in minutes from the expected report time, up to a maximum of 60. 4. Relation to the Publication These datasets were generated using the same simulation parameters described in the experimental section of the cited paper. They provide the underlying numerical data for Figure 3 in the publication (“Battery Charge Over Time” plots with user experience color mapping). Researchers can use these files to: Reproduce the plots, Compare new algorithms against the baseline results, Validate their own implementations, … 5. Licensing The dataset is released under the Creative Commons Attribution 4.0 International (CC BY 4.0) license. 6. Citation If you use this dataset, please cite both the dataset DOI and the original paper: Dataset citation (example): LOJDA, J., STRNADEL, J., SMRŽ, P., ŠIMEK, V. Simulation Outputs for the DYNAMIC Framework Study [Data set]. Zenodo. https://doi.org/10.5281/zenodo.16779333 Paper citation (example): LOJDA, J.; STRNADEL, J.; SMRŽ, P.; ŠIMEK, V. First Steps Towards Unified Low-Power IoT Design: The “DYNAMIC” Framework. 2024 IEEE East-West Design and Test Symposium, EWDTS 2024 - Proceedings. Yerevan: IEEE, 2024. p. 1–6. ISBN 979-8-3315-1576-8. 7. Acknowledgements This dataset was created as part of the LoLiPoP-IoT project (Long Life Power Platforms for Internet of Things, www.lolipop-iot.eu), grant agreement No. 101112286, which is jointly funded by the Chips Joint Undertaking and national public authorities. 8. Contact For questions or further information, please contact:Jakub Lojda, ilojda@fit.vut.czFaculty of Information Technology, Brno University of Technology, Bozetechova 2, 612 66 Brno, Czech Republic