N. Taherinejad, Peter R. Lewis, A. Jantsch, A. Rahmani, Lukas Esterle
{"title":"Resource Constrained Self-Aware Cyber-Physical Systems (Tutorial)","authors":"N. Taherinejad, Peter R. Lewis, A. Jantsch, A. Rahmani, Lukas Esterle","doi":"10.1109/FAS-W.2019.00071","DOIUrl":null,"url":null,"abstract":"The overlap of the two established fields of cyber-physical systems and self-aware computing systems constitutes a challenging class of systems that require autonomy and must satisfy multiple, possibly conflicting constraints (e.g., performance, timeliness, energy, reliability). Self-aware cyber-physical systems are situated in dynamic physical environments and constrained in their resources, they understand their own state and that of their environment. Based on that understanding, they are able to make appropriate decisions autonomously at runtime with high efficiency. In this tutorial, we will review the state of the art of this exciting domain.","PeriodicalId":368308,"journal":{"name":"2019 IEEE 4th International Workshops on Foundations and Applications of Self* Systems (FAS*W)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE 4th International Workshops on Foundations and Applications of Self* Systems (FAS*W)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FAS-W.2019.00071","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The overlap of the two established fields of cyber-physical systems and self-aware computing systems constitutes a challenging class of systems that require autonomy and must satisfy multiple, possibly conflicting constraints (e.g., performance, timeliness, energy, reliability). Self-aware cyber-physical systems are situated in dynamic physical environments and constrained in their resources, they understand their own state and that of their environment. Based on that understanding, they are able to make appropriate decisions autonomously at runtime with high efficiency. In this tutorial, we will review the state of the art of this exciting domain.