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

Publikation: Bidrag til bog/antologi/rapport/proceeding › Konferencebidrag i proceedings › Forskning › peer review

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DOI

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 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 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.
OriginalsprogEngelsk
Titel2020 IEEE Global Communications Conference, GLOBECOM 2020 - Proceedings
ForlagIEEE
Udgivelsesår2020
Artikelnummer9348074
ISBN (Elektronisk)978-1-7281-8298-8
DOI
StatusUdgivet - 2020
Begivenhed2020 IEEE Global Communications Conference - Taipei, Taiwan + Online (Hybrid), Taipei, Taiwan
Varighed: 7 dec. 2020 → 11 dec. 2020
https://globecom2020.ieee-globecom.org/

Konference

Konference2020 IEEE Global Communications Conference
LokationTaipei, Taiwan + Online (Hybrid)
LandTaiwan
ByTaipei
Periode07/12/2020 → 11/12/2020
Internetadresse
SerietitelIEEE Global Communications Conference (GLOBECOM)
ISSN1930-529X

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