LiME: The Linux Real-Time Task Model Extractor

We present LIME, a novel dynamic real-time task model extractor. LIME observes the temporal behavior of Linux real-time threads and automatically maps the observed activity to established real-time task models: sporadic and periodic tasks, upper and lower arrival curves, cumulative execution-time cu...

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Bibliographic Details
Published inProceedings / IEEE Real-Time and Embedded Technology and Applications Symposium pp. 255 - 269
Main Authors Brandenburg, Bjorn B., Courtaud, Cedric, Markovic, Filip, Ye, Bite
Format Conference Proceeding
LanguageEnglish
Published IEEE 06.05.2025
Subjects
ebpf
event-arrival curve
Kernel
Linux
Low latency communication
Measurement
measurement-based parameter estimation
model extraction
model inference
Monitoring
periodic tasks
Real-time systems
real-time task models
self-suspensions
Semantics
sporadic tasks
Synchronization
Testing
tracing
Vehicle dynamics
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Summary:We present LIME, a novel dynamic real-time task model extractor. LIME observes the temporal behavior of Linux real-time threads and automatically maps the observed activity to established real-time task models: sporadic and periodic tasks, upper and lower arrival curves, cumulative execution-time curves, and two self-suspension models (dynamic and segmented). LIME runs on unmodified Linux kernels and requires neither knowledge of real-time theory nor familiarity with Linux internals to be used effectively. An extensive evaluation shows LIME to achieve very high inference accuracy-in particular 100% accuracy for common automotive periods-with low kernel overhead, low latency impact, and low processor utilization (at best-effort priority).
ISSN:2642-7346
DOI:10.1109/RTAS65571.2025.00033