RASA: Reliability-Aware Scheduling Approach for FPGA-Based Resilient Embedded Systems in Extreme Environments

Field-programmable gate arrays (FPGAs) offer the flexibility of general-purpose processors along with the performance efficiency of dedicated hardware that essentially renders it as a platform of choice for modern-day robotic systems for achieving real-time performance. Such robotic systems when dep...

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Bibliographic Details
Published in:IEEE transactions on systems, man, and cybernetics. Systems man, and cybernetics. Systems, 2022-06, Vol.52 (6), p.3885-3899
Main Authors: Saha, Sangeet, Zhai, Xiaojun, Ehsan, Shoaib, Majeed, Shakaiba, McDonald-Maier, Klaus
Format: Article
Language:English
Subjects:
Embedded systems
Extreme environments
Extreme environments (EEs)
Fault detection
Fault tolerant systems
Field programmable gate arrays
field-programmable gate array (FPGA)
Hardware
partial reconfiguration
Preempting
Real time
real-time scheduling
Real-time systems
Reliability
resilient systems
Robots
Run time (computers)
Schedules
single-event upsets (SEUs)
Task analysis
Task scheduling
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Summary:Field-programmable gate arrays (FPGAs) offer the flexibility of general-purpose processors along with the performance efficiency of dedicated hardware that essentially renders it as a platform of choice for modern-day robotic systems for achieving real-time performance. Such robotic systems when deployed in harsh environments often get plagued by faults due to extreme conditions. Consequently, the real-time applications running on FPGA become susceptible to errors which call for a reliability-aware task scheduling approach, the focus of this article. We attempt to address this challenge using a hybrid offline-online approach. Given a set of periodic real-time tasks that require to be executed, the offline component generates a feasible preemptive schedule with specific preemption points. At runtime, these preemption events are utilized for fault detection. Upon detecting any faulty execution at such distinct points, the reliability-aware scheduling approach, RASA, orchestrates the recovery mechanism to remediate the scenario without jeopardizing the predefined schedule. Effectiveness of the proposed strategy has been verified through simulation-based experiments and we observed that the RASA is able to achieve 72% of task acceptance rate even under 70% of system workloads with high fault occurrence rates.
ISSN:2168-2216
2168-2232
DOI:10.1109/TSMC.2021.3077697