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A novel analytical method for worst case response time estimation of distributed embedded systems
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Kim, Jinwoo | - |
| dc.contributor.author | Oh, Hyunok | - |
| dc.contributor.author | Choi, Junchul | - |
| dc.contributor.author | Ha, Hyojin | - |
| dc.contributor.author | Ha, Soonhoi | - |
| dc.date.accessioned | 2022-07-16T10:03:11Z | - |
| dc.date.available | 2022-07-16T10:03:11Z | - |
| dc.date.issued | 2013-05 | - |
| dc.identifier.issn | 0738-100X | - |
| dc.identifier.issn | 0146-7123 | - |
| dc.identifier.uri | https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/162829 | - |
| dc.description.abstract | In this paper, we propose a novel analytical method, called scheduling time bound analysis, to find a tight upper bound of the worst-case response time in a distributed real-time embedded system, considering execution time variations of tasks, jitter of input arrivals, and scheduling anomaly behavior in a multi-tasking system all together. By analyzing the graph topology and worstcase scheduling scenarios, we measure the conservative scheduling time bound of each task. The proposed method supports an arbitrary mixture of preemptive and non-preemptive processing elements. Its speed is comparable to compositional approaches while it gives a much tighter bound. The advantages of the proposed approach compared with related work were verified by experimental results with randomly generated task graphs and a real-life automotive application. | - |
| dc.format.extent | 10 | - |
| dc.language | 영어 | - |
| dc.language.iso | ENG | - |
| dc.title | A novel analytical method for worst case response time estimation of distributed embedded systems | - |
| dc.type | Article | - |
| dc.identifier.doi | 10.1145/2463209.2488893 | - |
| dc.identifier.scopusid | 2-s2.0-84879873017 | - |
| dc.identifier.bibliographicCitation | Proceedings - Design Automation Conference, pp 1 - 10 | - |
| dc.citation.title | Proceedings - Design Automation Conference | - |
| dc.citation.startPage | 1 | - |
| dc.citation.endPage | 10 | - |
| dc.type.docType | Conference Paper | - |
| dc.description.isOpenAccess | N | - |
| dc.description.journalRegisteredClass | scopus | - |
| dc.subject.keywordPlus | Analytical method | - |
| dc.subject.keywordPlus | Arbitrary mixtures | - |
| dc.subject.keywordPlus | Automotive applications | - |
| dc.subject.keywordPlus | Distributed embedded system | - |
| dc.subject.keywordPlus | Distributed real-time embedded systems | - |
| dc.subject.keywordPlus | Performance analysis | - |
| dc.subject.keywordPlus | Processing elements | - |
| dc.subject.keywordPlus | Worst case response time | - |
| dc.subject.keywordPlus | Computer aided design | - |
| dc.subject.keywordPlus | Scheduling | - |
| dc.subject.keywordPlus | Topology | - |
| dc.subject.keywordPlus | Embedded systems | - |
| dc.subject.keywordAuthor | Distributed embedded system | - |
| dc.subject.keywordAuthor | Performance analysis | - |
| dc.subject.keywordAuthor | Worst case response time | - |
| dc.identifier.url | https://dl.acm.org/doi/10.1145/2463209.2488893 | - |
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