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Schedulability analysis using two clocks

  • Elena Fersman*
  • , Leonid Mokrushin
  • , Paul Pettersson
  • , Wang Yi
  • *此作品的通讯作者
  • Uppsala University

科研成果: 书/报告/会议事项章节章节同行评审

摘要

In classic scheduling theory, real-time tasks are usually assumed to be periodic, i.e. tasks arrive and compute with fixed rates periodically. To relax the stringent constraints on task arrival times, we propose to use timed automata to describe task arrival patterns. In a previous work, it is shown that the general schedulability checking problem for such models is a reachability problem for a decidable class of timed automata extended with subtraction. Unfortunately, the number of clocks needed in the analysis is proportional to the maximal number of schedulable task instances associated with a model, which in many cases is huge. In this paper, we show that for fixed priority scheduling strategy, the schedulability checking problem can be solved by reachability analysis on standard timed automata using only two extra clocks in addition to the clocks used in the original model to describe task arrival times. The analysis can be done in a similar manner to response time analysis in classic Rate-Monotonic Scheduling. We believe that this is the optimal solution to the problem, a problem that was suspected undecidable previously. We also extend the result to systems in which the timed automata and the tasks may read and update shared data variables. Then the release time-point of a task may depend on the values of the shared variables, and hence on the time-point at which other tasks finish their exection. We show that this schedulability problem can be encoded as timed automata using n+1 extra clocks, where n is the number of tasks.

源语言英语
主期刊名Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
编辑Hubert Garavel, John Hatcliff
出版商Springer Verlag
224-239
页数16
ISBN(印刷版)3540008985
DOI
出版状态已出版 - 2003
已对外发布

出版系列

姓名Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
2619
ISSN(印刷版)0302-9743
ISSN(电子版)1611-3349

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