Projekter pr. år
Abstract
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.
Originalsprog | Engelsk |
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Titel | 2020 IEEE Global Communications Conference, GLOBECOM 2020 - Proceedings |
Forlag | IEEE |
Publikationsdato | 2020 |
Artikelnummer | 9348074 |
ISBN (Elektronisk) | 978-1-7281-8298-8 |
DOI | |
Status | Udgivet - 2020 |
Begivenhed | 2020 IEEE Global Communications Conference - Taipei, Taiwan + Online (Hybrid), Taipei, Taiwan Varighed: 7 dec. 2020 → 11 dec. 2020 https://globecom2020.ieee-globecom.org/ |
Konference
Konference | 2020 IEEE Global Communications Conference |
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Lokation | Taipei, Taiwan + Online (Hybrid) |
Land/Område | Taiwan |
By | Taipei |
Periode | 07/12/2020 → 11/12/2020 |
Internetadresse |
Navn | IEEE Global Communications Conference (GLOBECOM) |
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ISSN | 1930-529X |
Fingeraftryk
Dyk ned i forskningsemnerne om 'Memory-aware Online Compression of CAN Bus Data for Future Vehicular Systems'. Sammen danner de et unikt fingeraftryk.Projekter
- 2 Afsluttet
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SCALE-loT - Scalable Systems for Massive loT
Lucani Rötter, D. E. (Deltager)
SCALE-loT - Scalable Systems for Massive loT
01/01/2019 → 31/12/2022
Projekter: Projekt › Forskning
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