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
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 50 条
  • [1] Soft and Hard Reliability-Aware Scheduling for Multicore Embedded Systems with Energy Harvesting
    Xiang, Yi
    Pasricha, Sudeep
    IEEE TRANSACTIONS ON MULTI-SCALE COMPUTING SYSTEMS, 2015, 1 (04): : 220 - 235
  • [2] Real-Time Application Processing for FPGA-Based Resilient Embedded Systems in Harsh Environments
    Saha, Sangeet
    Ehsan, Shoaib
    Stoica, Adrian
    Stolkin, Rustam
    McDonald-Maier, Klaus
    2018 NASA/ESA CONFERENCE ON ADAPTIVE HARDWARE AND SYSTEMS (AHS 2018), 2018, : 299 - 304
  • [3] Reliability-aware Co-synthesis for Embedded Systems
    Y. Xie
    L. Li
    M. Kandemir
    N. Vijaykrishnan
    M. J. Irwin
    The Journal of VLSI Signal Processing Systems for Signal, Image, and Video Technology, 2007, 49 : 87 - 99
  • [4] Reliability-aware co-synthesis for embedded systems
    Xie, Y.
    Li, L.
    Kandemir, M.
    Vijaykrishnan, N.
    Irwin, M. J.
    JOURNAL OF VLSI SIGNAL PROCESSING SYSTEMS FOR SIGNAL IMAGE AND VIDEO TECHNOLOGY, 2007, 49 (01): : 87 - 99
  • [5] Reliability-aware co-synthesis for embedded systems
    Xie, Y
    Li, L
    Kandemir, M
    Vijaykrishnan, N
    Irwin, MJ
    15TH IEEE INTERNATIONAL CONFERENCE ON APPLICATION-SPECIFIC SYSTEMS, ARCHITECTURES AND PROCESSORS, PROCEEDINGS, 2004, : 41 - 50
  • [6] A Reliability-aware Task Scheduling Algorithm Based on Replication on Heterogeneous Computing Systems
    Wang, Shuli
    Li, Kenli
    Mei, Jing
    Xiao, Guoqing
    Li, Keqin
    JOURNAL OF GRID COMPUTING, 2017, 15 (01) : 23 - 39
  • [7] A Reliability-aware Task Scheduling Algorithm Based on Replication on Heterogeneous Computing Systems
    Shuli Wang
    Kenli Li
    Jing Mei
    Guoqing Xiao
    Keqin Li
    Journal of Grid Computing, 2017, 15 : 23 - 39
  • [8] Reliability-aware scheduling strategy for heterogeneous distributed computing systems
    Tang, Xiaoyong
    Li, Kenli
    Li, Renfa
    Veeravalli, Bharadwaj
    JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING, 2010, 70 (09) : 941 - 952
  • [9] A Fault Analysis and Classifier Framework for Reliability-aware SRAM-based FPGA Systems
    Bolchini, Cristiana
    Castro, Fabrizio
    Miele, Antonio
    IEEE INTERNATIONAL SYMPOSIUM ON DEFECT AND FAULT TOLERANCE VLSI SYSTEMS, PROCEEDINGS, 2009, : 173 - 181
  • [10] A Current Consumption Measurement Approach for FPGA-Based Embedded Systems
    Nakutis, Zilvinas
    IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2013, 62 (05) : 1130 - 1137