{"title":"A precise schedulability test algorithm for scheduling periodic tasks in real-time systems","authors":"Wan-Chen Lu, Jen-Wei Hsieh, W. Shih","doi":"10.1145/1141277.1141616","DOIUrl":null,"url":null,"abstract":"Rate monotonic analysis (RMA) has been shown to be effective in the schedulability analysis of various types of system. This paper focuses on reducing the run time of each RMA-tested system. Based on a new concept of tasks, denoted by the lift-utilization tasks, we propose a novel method to reduce the number of iterative calculations in the derivation of the worst-case response time of each task in its RMA test. The capability of the proposed method was evaluated and compared to related work, which revealed that our method produced savings of 26-33% in the number of RMA iterations.","PeriodicalId":269830,"journal":{"name":"Proceedings of the 2006 ACM symposium on Applied computing","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2006-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2006 ACM symposium on Applied computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/1141277.1141616","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9
Abstract
Rate monotonic analysis (RMA) has been shown to be effective in the schedulability analysis of various types of system. This paper focuses on reducing the run time of each RMA-tested system. Based on a new concept of tasks, denoted by the lift-utilization tasks, we propose a novel method to reduce the number of iterative calculations in the derivation of the worst-case response time of each task in its RMA test. The capability of the proposed method was evaluated and compared to related work, which revealed that our method produced savings of 26-33% in the number of RMA iterations.