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Network-Centric Approach Using Task Migration for Drive-by-Wire Vehicle Resilience

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dc.contributor.authorBaik,Jeanseong-
dc.contributor.authorJeong,Haegeon-
dc.contributor.authorKang,Kyungtae-
dc.date.accessioned2023-09-04T05:35:31Z-
dc.date.available2023-09-04T05:35:31Z-
dc.date.issued2020-10-
dc.identifier.urihttps://scholarworks.bwise.kr/erica/handle/2021.sw.erica/114647-
dc.description.abstractThe electronic control unit (ECU), considered the brain of a vehicle, suffers from a design problem called single point of failure (SPOF), which can induce system malfunctions. This problem can be addressed via redundancy, which increases the reliability of a mission-critical system by allowing multiple ECUs to perform a single function. However, this solution requires additional ECU and maintenance costs incurred by the redundant ECUs. A cost-effective approach for improving safety is to utilize the network connectivity between existing ECUs. In this paper, we propose a method that migrates critical tasks residing in an infeasible ECU to a replaceable ECU by using the network connection between them. Furthermore, to demonstrate the feasibility of the method, we implemented a task migration method on a Lego vehicle composed of three ECUs to prevent sudden unintended acceleration accidents caused by faults in an ECU managing the acceleration task.-
dc.format.extent2-
dc.language영어-
dc.language.isoENG-
dc.publisherIEEE COMPUTER SOC-
dc.titleNetwork-Centric Approach Using Task Migration for Drive-by-Wire Vehicle Resilience-
dc.typeArticle-
dc.publisher.location미국-
dc.identifier.doi10.1109/ICNP49622.2020.9259350-
dc.identifier.bibliographicCitation2020 IEEE 28th International Conference on Network Protocols (ICNP), v.NA, no.NA, pp 1 - 2-
dc.citation.title2020 IEEE 28th International Conference on Network Protocols (ICNP)-
dc.citation.volumeNA-
dc.citation.numberNA-
dc.citation.startPage1-
dc.citation.endPage2-
dc.type.docTypeProceeding-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassother-
dc.subject.keywordAuthorTask migration-
dc.subject.keywordAuthorRedundancy-
dc.subject.keywordAuthorResilience-
dc.subject.keywordAuthorHigh reliability-
dc.identifier.urlhttps://ieeexplore.ieee.org/document/9259350?arnumber=9259350&SID=EBSCO:edseee-
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ERICA 소프트웨어융합대학 (DEPARTMENT OF ARTIFICIAL INTELLIGENCE)
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