{"title":"Stochastic response-time guarantee for non-preemptive, fixed-priority scheduling under errors","authors":"Philip Axer, R. Ernst","doi":"10.1145/2463209.2488946","DOIUrl":null,"url":null,"abstract":"Error recovery mechanisms, such as automatic repeat request (ARQ) for e.g. the CAN protocol, are a crucial part of safety critical embedded systems. These can have a strong impact on the timing behavior of the system and an unpropitious combination of error events may cause a real-time application to miss deadlines with potentially hazardous consequences. Therefore, formal analysis of the worst-case timing including errors is indispensable for certification. We present a new convolution-based stochastic analysis in which we model errors as additional execution time to bound the probability for an activation to exceed a response-time value in the worst-case.","PeriodicalId":320207,"journal":{"name":"2013 50th ACM/EDAC/IEEE Design Automation Conference (DAC)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"17","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 50th ACM/EDAC/IEEE Design Automation Conference (DAC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2463209.2488946","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 17
Abstract
Error recovery mechanisms, such as automatic repeat request (ARQ) for e.g. the CAN protocol, are a crucial part of safety critical embedded systems. These can have a strong impact on the timing behavior of the system and an unpropitious combination of error events may cause a real-time application to miss deadlines with potentially hazardous consequences. Therefore, formal analysis of the worst-case timing including errors is indispensable for certification. We present a new convolution-based stochastic analysis in which we model errors as additional execution time to bound the probability for an activation to exceed a response-time value in the worst-case.