Research
Lightweight Compression for Severely Constrained IoT Devices
Research output: Contribution to book/anthology/report/proceeding › Article in proceedings › Research › peer-review
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European Wireless Conference 2022. IEEE, 2022.
Research output: Contribution to book/anthology/report/proceeding › Article in proceedings › Research › peer-review
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TY - GEN
T1 - Lightweight Compression for Severely Constrained IoT Devices
AU - Vestergaard, Rasmus
AU - Techel, Johannes
AU - Zhang, Qi
AU - Lucani Rötter, Daniel Enrique
PY - 2022
Y1 - 2022
N2 - In this paper, we propose S-BP (Sensor Bit-Packing), a lightweight data compression scheme with a tiny memory footprint. Due to its low resource usage, the method is particularly suited for resource-constrained IoT sensor nodes. S-BP excels for small data windows in the tens or hundreds of bytes, enabling both compression and energy savings even when collected data must be transmitted frequently. We implemented the proposed algorithm for Contiki OS, proving its suitability for severely constrained devices and allowing us to use real-world data to evaluate it in terms of the achieved compression, processing speed, and energy usage. For sensor data, S-BP achieves comparable and even better compression compared to more resource-intensive compressors designed for powerful devices. We also experience that energy savings are achieved as soon as the compressed size is just 2 % less than the original.
AB - In this paper, we propose S-BP (Sensor Bit-Packing), a lightweight data compression scheme with a tiny memory footprint. Due to its low resource usage, the method is particularly suited for resource-constrained IoT sensor nodes. S-BP excels for small data windows in the tens or hundreds of bytes, enabling both compression and energy savings even when collected data must be transmitted frequently. We implemented the proposed algorithm for Contiki OS, proving its suitability for severely constrained devices and allowing us to use real-world data to evaluate it in terms of the achieved compression, processing speed, and energy usage. For sensor data, S-BP achieves comparable and even better compression compared to more resource-intensive compressors designed for powerful devices. We also experience that energy savings are achieved as soon as the compressed size is just 2 % less than the original.
M3 - Article in proceedings
BT - European Wireless Conference 2022
PB - IEEE
ER -