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

被引:13
作者
Saha, Sangeet [1 ]
Zhai, Xiaojun [1 ]
Ehsan, Shoaib [1 ]
Majeed, Shakaiba [2 ]
McDonald-Maier, Klaus [1 ]
机构
[1] Univ Essex, Embedded & Intelligent Syst Lab, Colchester CO4 3SQ, Essex, England
[2] Hanyang Univ, Real Time Comp & Commun Lab, Seoul 04763, South Korea
来源
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS | 2022年 / 52卷 / 06期
基金
英国工程与自然科学研究理事会;
关键词
Field programmable gate arrays; Task analysis; Real-time systems; Robots; Hardware; Fault tolerant systems; Schedules; Extreme environments (EEs); field-programmable gate array (FPGA); partial reconfiguration; real-time scheduling; reliability; resilient systems; single-event upsets (SEUs); TASKS;
D O I
10.1109/TSMC.2021.3077697
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页码:3885 / 3899
页数:15
相关论文
共 36 条
[11]  
Happe Markus, 2015, Applied Reconfigurable Computing. 11th International Symposium, ARC 2015. Proceedings: LNCS 9040, P79, DOI 10.1007/978-3-319-16214-0_7
[12]  
Haque MA, 2014, IEEE REAL TIME, P63, DOI 10.1109/RTAS.2014.6925991
[13]  
Jin J., 2013, P 7 INT C UB INF MAN, P80
[14]   Distributed Task Allocation of Multiple Robots: A Control Perspective [J].
Jin, Long ;
Li, Shuai .
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2018, 48 (05) :693-701
[15]   Comparison of Preemption Schemes for Partially Reconfigurable FPGAs [J].
Jozwik, Krzysztof ;
Tomiyama, Hiroyuki ;
Edahiro, Masato ;
Honda, Shinya ;
Takada, Hiroaki .
IEEE EMBEDDED SYSTEMS LETTERS, 2012, 4 (02) :45-48
[16]  
Khaluf, 2014, THESIS U PADERBORN P
[17]  
Khuat Quang-Hai, 2013, 2013 Conference on Design and Architectures for Signal and Image Processing (DASIP), P265
[18]   Multiobjective Optimization Approach for a Portable Development of Reconfigurable Real-Time Systems: From Specification to Implementation [J].
Lakhdhar, Wafa ;
Mzid, Rania ;
Khalgui, Mohamed ;
Li, Zhiwu ;
Frey, Georg ;
Al-Ahmari, Abdulrahman .
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2019, 49 (03) :623-637
[19]   An Efficient Task Placement Method for Reconfigurable FPGA Systems [J].
Lee, Trong-Yen ;
Lin, Nian-You ;
Chen, Wei-Cheng ;
Wu, Haixia .
2013 SEVENTH INTERNATIONAL CONFERENCE ON COMPLEX, INTELLIGENT, AND SOFTWARE INTENSIVE SYSTEMS (CISIS), 2013, :451-455
[20]  
Maillard Pierre, 2018, 2018 IEEE Nuclear & Space Radiation Effects Conference (NSREC 2018), DOI 10.1109/NSREC.2018.8584298