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Title: Pythia-MCS: Enabling Quarter-Clairvoyance in I/O-Driven Mixed-Criticality Systems
In mixed-criticality systems, mode switch is a key strategy which dynamically provides a balance between system performance and safety. In conventional MCS frameworks, mode switch is triggered by the over-execution of a task; i.e., a task overruns the less pessimistic worst-case execution time. In cyber-physical systems, the data volume generated by I/O affects and can even dominate task computation time. With this in mind, we introduce a novel MCS architecture, termed Pythia-MCS, which predicts task execution time according to I/O run-time behaviors. With the new feature of future-prediction, the Pythia-MCS provides more timely, but still accurate, mode switch. We also present a new theoretical model (quarter-clairvoyance), which guarantees the timing predictability of the design, and a new schedulability analysis for the Pythia-MCS, which demonstrates improved schedulability compared to conventional MCS frameworks. The Pythia-MCS is the first MCS framework enabling the clairvoyance functionality.
Authors:
; ; ; ;
Award ID(s):
1724227
Publication Date:
NSF-PAR ID:
10288528
Journal Name:
2020 IEEE Real-Time Systems Symposium (RTSS)
Page Range or eLocation-ID:
38 to 50
Sponsoring Org:
National Science Foundation
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