LiPar: A Lightweight Parallel Learning Model for Practical In-Vehicle Network Intrusion Detection

A Zhang, K Wang, B Wang, Y Wu - arXiv preprint arXiv:2311.08000, 2023 - arxiv.org
With the development of intelligent transportation systems, vehicles are exposed to a
complex network environment. As the main network of in-vehicle networks, the controller …

Dynamic scheduling algorithm for a utomotive safety critical systems

VP Kumar, AS Pillai - 2020 Fourth International Conference on …, 2020 - ieeexplore.ieee.org
The automotive industry is one of the fastest-growing sectors in terms of usage of
technology. Most of the real time systems in automobiles are hard real time in nature due to …

Thermal aware lifetime reliability optimization for automotive distributed computing applications

AS Bankar, S Sha, V Chaturvedi… - 2020 IEEE 38th …, 2020 - ieeexplore.ieee.org
As the automotive industry is moving towards electric and self-driving vehicles, how to
ensure the high degree of reliability for electronic control systems (ECS) has emerged as a …

A Generalistic Approach to Machine-Learning-Supported Task Migration on Real-Time Systems

O Delgadillo, B Blieninger, J Kuhn… - Journal of Low Power …, 2022 - mdpi.com
Consolidating tasks to a smaller number of electronic control units (ECUs) is an important
strategy for optimizing costs and resources in the automotive industry. In our research, we …

Online Test Scheduling in Car Production Lines

S König, B Vogel-Heuser, F Karg… - 2023 IEEE Intelligent …, 2023 - ieeexplore.ieee.org
Cars with software-intensive features such as autonomous driving bring new opportunities to
Original Equipment Manufacturers (OEMs) and their manufacturing processes. The …

A Framework for Tasks Allocation and Scheduling in Precision Agriculture Settings

M Santilli, RF Carpio, A Gasparri - 2021 20th International …, 2021 - ieeexplore.ieee.org
This paper proposes an allocation and scheduling framework to assign to robotics platforms
and human operators the farming operations required by the decision-support system being …

A Core-Combine Processing Method for Diagnostic in Multi-core ECU

SJ Lim, SB Oh, YS Do, JW Jeon - 2024 IEEE 33rd International …, 2024 - ieeexplore.ieee.org
With the increasing data processing demands driven by features like ADAS and infotainment
in the automotive industry, there'sa trend toward expanding the number of cores to cope with …

Thermal Aware System-Wide Reliability Optimization for Automotive Distributed Computing Applications

AS Bankar, S Sha, J Bhimani… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
As the automotive industry is shifting the paradigm towards autonomous driving, safety
guarantee has become a paramount consideration. Temperature plays a key role in the …

Fault Analysis and Debugging of Intelligent Connected Car Wire-Controlled Chassis System

G Shun, MAM Norman… - 2024 5th International …, 2024 - ieeexplore.ieee.org
This research study deals with the fault analysis and troubleshooting of the electronically
controlled chassis system of the intelligent connected vehicle. The author first emphasizes …

An Architecture to Enable Machine-Learning-Based Task Migration for Multi-Core Real-Time Systems

O Delgadillo, B Blieninger, J Kuhn… - 2021 IEEE 14th …, 2021 - ieeexplore.ieee.org
ECU consolidation is an automotive trend that tends to reduce the number of electronic
devices in a vehicle to optimize resources and costs. However, its implementation …