{"title":"Analysis of real-time multi-modal FP-scheduled systems with non-preemptible regions","authors":"Masud Ahmed, P. Hettiarachchi, N. Fisher","doi":"10.1109/RTAS.2015.7108415","DOIUrl":null,"url":null,"abstract":"Over the years, multiple hardware and software operating modes have been employed in many computing devices (e.g., tablets, smart-phones, GPS receivers) to efficiently utilize device resources. Similar advantages are also preferred in realtime systems (RTS) due to the requirement that a RTS must respond in a timely manner to a physical environment that may change sporadically. An efficient multi-modal system (MMS) is also a prerequisite for the development of real-time control systems which can maintain stable system behavior while ensuring timing guarantees for a changing set of real-time tasks. However, the currently-available fixed-priority (FP) schedulability analysis for multi-modal systems with both software/hardware modes is computationally expensive. In addition, current schedulability analysis for systems that support mode changes requires an assumption that is often not suitable for cyber-physical systems (CPS): sensing and actuation in the underlying physical plant are preemptible activities. However, sensors such as radar transmitter/ receiver requires non-preemptible access to the processor upon sending and then processing the return signal for accuracy. In this research, we develop a framework for multi-modal RTS scheduled by FP algorithm along with efficient schedulability analysis with pseudo-polynomial complexity considering the advantages and limitations of specific software/hardware model. Two simulations: a case study on adaptive cruise control in automotive systems, and schedulability comparison are included to corroborate the performance of the schedulability analysis.","PeriodicalId":320300,"journal":{"name":"21st IEEE Real-Time and Embedded Technology and Applications Symposium","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"21st IEEE Real-Time and Embedded Technology and Applications Symposium","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RTAS.2015.7108415","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
Over the years, multiple hardware and software operating modes have been employed in many computing devices (e.g., tablets, smart-phones, GPS receivers) to efficiently utilize device resources. Similar advantages are also preferred in realtime systems (RTS) due to the requirement that a RTS must respond in a timely manner to a physical environment that may change sporadically. An efficient multi-modal system (MMS) is also a prerequisite for the development of real-time control systems which can maintain stable system behavior while ensuring timing guarantees for a changing set of real-time tasks. However, the currently-available fixed-priority (FP) schedulability analysis for multi-modal systems with both software/hardware modes is computationally expensive. In addition, current schedulability analysis for systems that support mode changes requires an assumption that is often not suitable for cyber-physical systems (CPS): sensing and actuation in the underlying physical plant are preemptible activities. However, sensors such as radar transmitter/ receiver requires non-preemptible access to the processor upon sending and then processing the return signal for accuracy. In this research, we develop a framework for multi-modal RTS scheduled by FP algorithm along with efficient schedulability analysis with pseudo-polynomial complexity considering the advantages and limitations of specific software/hardware model. Two simulations: a case study on adaptive cruise control in automotive systems, and schedulability comparison are included to corroborate the performance of the schedulability analysis.