Abdeldjalil Boudjadar, Alexandre David, J. H. Kim, K. Larsen, Marius Mikucionis, Ulrik Nyman, A. Skou
{"title":"具有概率偶发任务的混合临界实时系统的可调度度","authors":"Abdeldjalil Boudjadar, Alexandre David, J. H. Kim, K. Larsen, Marius Mikucionis, Ulrik Nyman, A. Skou","doi":"10.1109/TASE.2014.27","DOIUrl":null,"url":null,"abstract":"We present the concept of degree of schedulability for mixed-criticality scheduling systems. This concept is given in terms of the two factors 1) Percentage of Missed Deadlines (PoMD), and 2) Degradation of the Quality of Service (DoQoS). The novel aspect is that we consider task arrival patterns that follow user-defined continuous probability distributions. We determine the degree of schedulability of a single scheduling component which can contain both periodic and sporadic tasks using statistical model checking in the form of UPPAAL SMC. We support uniform, exponential, Gaussian and any user-defined probability distribution.","PeriodicalId":371040,"journal":{"name":"2014 Theoretical Aspects of Software Engineering Conference","volume":"422 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":"{\"title\":\"Degree of Schedulability of Mixed-Criticality Real-Time Systems with Probabilistic Sporadic Tasks\",\"authors\":\"Abdeldjalil Boudjadar, Alexandre David, J. H. Kim, K. Larsen, Marius Mikucionis, Ulrik Nyman, A. Skou\",\"doi\":\"10.1109/TASE.2014.27\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We present the concept of degree of schedulability for mixed-criticality scheduling systems. This concept is given in terms of the two factors 1) Percentage of Missed Deadlines (PoMD), and 2) Degradation of the Quality of Service (DoQoS). The novel aspect is that we consider task arrival patterns that follow user-defined continuous probability distributions. We determine the degree of schedulability of a single scheduling component which can contain both periodic and sporadic tasks using statistical model checking in the form of UPPAAL SMC. We support uniform, exponential, Gaussian and any user-defined probability distribution.\",\"PeriodicalId\":371040,\"journal\":{\"name\":\"2014 Theoretical Aspects of Software Engineering Conference\",\"volume\":\"422 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"13\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 Theoretical Aspects of Software Engineering Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/TASE.2014.27\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 Theoretical Aspects of Software Engineering Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TASE.2014.27","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Degree of Schedulability of Mixed-Criticality Real-Time Systems with Probabilistic Sporadic Tasks
We present the concept of degree of schedulability for mixed-criticality scheduling systems. This concept is given in terms of the two factors 1) Percentage of Missed Deadlines (PoMD), and 2) Degradation of the Quality of Service (DoQoS). The novel aspect is that we consider task arrival patterns that follow user-defined continuous probability distributions. We determine the degree of schedulability of a single scheduling component which can contain both periodic and sporadic tasks using statistical model checking in the form of UPPAAL SMC. We support uniform, exponential, Gaussian and any user-defined probability distribution.