Memory and time-efficient schedulability analysis of task sets with stochastic execution time
- 13 November 2002
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
Abstract
This paper presents an efficient way to analyse the performance of task sets, where the task execution time is specified as a generalized continuous probability distribution. We consider fixed task sets of periodic, possibly dependent, non-pre-emptable tasks with deadlines less than or equal to the period. Our method is not restricted to any specific scheduling policy and supports policies with both dynamic and static priorities. An algorithm to construct the underlying stochastic process in a memory and time efficient way is presented. We discuss the impact of various parameters on complexity, in terms of analysis time and required memory. Experimental results show the efficiency of the proposed approach.Keywords
This publication has 10 references indexed in Scilit:
- A probabilistic performance metric for real-time system designPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2003
- Statistical rate monotonic schedulingPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- FFTW: an adaptive software architecture for the FFTPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Probabilistic performance guarantee for real-time tasks with varying computation timesPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Assessing Probabilistic Timing Constraints on System PerformanceDesign Automation for Embedded Systems, 2000
- Integrating multimedia applications in hard real-time systemsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1998
- Real-Time Schedulability Tests for Preemptive MultitaskingReal-Time Systems, 1998
- Scheduling aperiodic tasks in dynamic priority systemsReal-Time Systems, 1996
- Implications of classical scheduling results for real-time systemsComputer, 1995
- Fixed priority pre-emptive scheduling: An historical perspectiveReal-Time Systems, 1995