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Seunggon Kim

dblp:213/8299 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2017
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems
1 paper
Embedded and real-time systems · 64% Performance modeling and evaluation · 28% GPUs and heterogeneous computing · 8%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Embedded and real-time systems
automotive systems
0.312017
Functionally and Temporally Correct Simulation of Cyber-Systems for Automotive Systems · RTSS 2017
Embedded and real-time systems
cyber-physical systems
0.312017
Functionally and Temporally Correct Simulation of Cyber-Systems for Automotive Systems · RTSS 2017
Performance modeling and evaluation
simulation
0.312017
Functionally and Temporally Correct Simulation of Cyber-Systems for Automotive Systems · RTSS 2017
GPUs and heterogeneous computing
preemption
0.112017
Functionally and Temporally Correct Simulation of Cyber-Systems for Automotive Systems · RTSS 2017
Embedded and real-time systems
real-time scheduling
0.112017
Functionally and Temporally Correct Simulation of Cyber-Systems for Automotive Systems · RTSS 2017

Methods — techniques the papers use, named apart from their topics

scheduling · 0.3discrete-event simulation · 0.3
YearPublicationVenuePosition
2017 Functionally and Temporally Correct Simulation of Cyber-Systems for Automotive Systems
abstract
The current simulation tools used in the automotive industry do not correctly model timing behaviors of cyber-systems such as varying execution times and preemptions. Thus, they cannot correctly predict the real control performance. Motivated by this limitation, this paper proposes functionally and temporally correct simulation for the cyber-side of an automotive system. The key idea is to keep the data and time correctness only at physical interaction points and enjoy freedom of scheduling simulated jobs for all other cases. This way, the proposed approach significantly improves the real-time simulation capacity of the state-of-the-art simulation methods while keeping the functional and temporal correctness.
Kyoung-Soo We, Seunggon Kim, Chang-Gun Lee
RTSS2