首页|An efficient schedulability analysis based on worst-case interference time for real-time systems

An efficient schedulability analysis based on worst-case interference time for real-time systems

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Real-time systems are widely implemented in the Internet of Things(IoT)and safety-critical systems,both of which have generated enormous social value.Aiming at the classic schedulability analysis problem in real-time systems,we proposed an exact Boolean analysis based on interference(EBAI)for schedulability analysis in real-time systems.EBAI is based on worst-case interference time(WCIT),which considers both the release jitter and blocking time of the task.We improved the efficiency of the three existing tests and provided a comprehensive summary of related research results in the field.Abundant experiments were conducted to compare EBAI with other related results.Our evaluation showed that in certain cases,the runtime gain achieved using our analysis method may exceed 73％compared to the state-of-the-art schedulability test.Furthermore,the benefits obtained from our tests grew with the number of tasks,reaching a level suitable for practical application.EBAI is oriented to the five-tuple real-time task model with stronger expression ability and possesses a low runtime overhead.These characteristics make it applicable in various real-time systems such as spacecraft,autonomous vehicles,industrial robots,and traffic command systems.

five-tuple real-time task modelreal-time systemspacecraftInternet of Thingsexact schedu-lability analysisworst-case interference time

Hongbiao LIU、Mengfei YANG、Lei QIAO、Xi CHEN、Jian GONG

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School of Computer Science and Technology,Xidian University,Xi'an 710071,China

China Academy of Space Technology,Beijing 100190,China

Beijing Institute of Control Engineering,Beijing 100080,China

National Natural Science Foundation of ChinaNational Natural Science Foundation of ChinaNational Natural Science Foundation of China

620320046180201761632005

2024

10.1007/s11432-022-3891-4

中国科学:信息科学(英文版)
中国科学院

中国科学:信息科学(英文版)

CSTPCDEI
影响因子：0.715
ISSN：1674-733X
年,卷(期)：2024.67(9)