Memory-aware Online Compression of CAN Bus Data for Future Vehicular Systems

TY - GEN

T1 - Memory-aware Online Compression of CAN Bus Data for Future Vehicular Systems

AU - Yazdani, Niloofar

AU - Nielsen, Lars

AU - Lucani Rötter, Daniel Enrique

PY - 2020

Y1 - 2020

N2 - Vehicles generate a large amount of data from their internal sensors. This data is not only useful for a vehicle's proper operation, but it provides car manufacturers with the ability to optimize the performance of individual vehicles and companies with fleets of vehicles (e.g., trucks, taxis, tractors) to optimize their operations to reduce fuel costs and plan repairs. This paper proposes algorithms to compress CAN bus data, specifically, packaged as MDF4 files. In particular, we propose lightweight, online and configurable compression algorithms that allow limited devices to choose the amount of RAM and flash memory allocated to them. We show that our proposals can outperform LZW for the same RAM footprint, and can even deliver comparable or better performance to DEFLATE under the same RAM limitations.

AB - Vehicles generate a large amount of data from their internal sensors. This data is not only useful for a vehicle's proper operation, but it provides car manufacturers with the ability to optimize the performance of individual vehicles and companies with fleets of vehicles (e.g., trucks, taxis, tractors) to optimize their operations to reduce fuel costs and plan repairs. This paper proposes algorithms to compress CAN bus data, specifically, packaged as MDF4 files. In particular, we propose lightweight, online and configurable compression algorithms that allow limited devices to choose the amount of RAM and flash memory allocated to them. We show that our proposals can outperform LZW for the same RAM footprint, and can even deliver comparable or better performance to DEFLATE under the same RAM limitations.

KW - CAN

KW - Controller Area Network

KW - IoT

KW - MDF4

KW - generalized deduplication

KW - limited RAM

KW - lossless compression

UR - http://www.scopus.com/inward/record.url?scp=85097614267&partnerID=8YFLogxK

U2 - 10.1109/GLOBECOM42002.2020.9348074

DO - 10.1109/GLOBECOM42002.2020.9348074

M3 - Article in proceedings

T3 - IEEE Global Communications Conference (GLOBECOM)

BT - 2020 IEEE Global Communications Conference, GLOBECOM 2020 - Proceedings

PB - IEEE

T2 - 2020 IEEE Global Communications Conference

Y2 - 7 December 2020 through 11 December 2020

ER -