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SACS: A Self-Adaptive Checkpointing Strategy for Microkernel-Based Intermittent Systems

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Published:01 August 2022Publication History

ABSTRACT

Intermittent systems are usually energy-harvesting embedded systems that harvest energy from ambient environment and perform computation intermittently. Due to the unreliable power, these intermittent systems typically adopt different checkpointing strategies for ensuring the data consistency and execution progress after the systems are resumed from unpredictable power failures. Existing checkpointing strategies are usually suitable for bare-metal intermittent systems with short run time. Due to the improvement of energy-harvesting techniques, intermittent systems are having longer run time and better computation power, so that more and more intermittent systems tend to function with a microkernel for handling more/multiple tasks at the same time. However, existing checkpointing strategies were not designed for (or aware of) such microkernel-based intermittent systems that support the running of multiple tasks, and thus have poor performance on preserving the execution progress. To tackle this issue, we propose a design, called self-adaptive checkpointing strategy (SACS), tailored for microkernel-based intermittent systems. By leveraging the time-slicing scheduler, the proposed design dynamically adjust the checkpointing interval at both run time and reboot time, so as to improve the system performance by achieving a good balance between the execution progress and the number of performed checkpoints. A series of experiments was conducted based on a development board of Texas Instrument (TI) with well-known benchmarks. Compared to the state-of-the-art designs, experiment results show that our design could reduce the execution time by at least 46.8% under different conditions of ambient environment while maintaining the number of performed checkpoints in an acceptable scale.

References

  1. S Ahmed, N. A. Bhatti, M. H. Alizai, J. H. Siddiqui, and L. Mottola. 2019. Efficient intermittent computing with differential checkpointing. In Proceedings of the 20th ACM SIGPLAN/SIGBED International Conference on Languages, Compilers, and Tools for Embedded Systems. 70–81.Google ScholarGoogle Scholar
  2. S. Beeby, M. Tudor, and N. White. 2006. Energy harvesting vibration sources for microsystems applications. Measurement science and technology 17, 12, R175.Google ScholarGoogle Scholar
  3. J. Choi, H. Joe, Y. Kim, and C. Jung. 2019. Achieving stagnation-free intermittent computation with boundary-free adaptive execution. In 2019 IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS). 331–344.Google ScholarGoogle Scholar
  4. A. Colin and B. Lucia. 2016. Chain: tasks and channels for reliable intermittent programs. In Proceedings of the 2016 ACM SIGPLAN International Conference on Object-Oriented Programming, Systems, Languages, and Applications. 514.Google ScholarGoogle Scholar
  5. Balsamo et al.2016. Hibernus++: a self-calibrating and adaptive system for transiently-powered embedded devices. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 35, 12(2016), 1968–1980.Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Guthaus et al.2001. MiBench: A free, commercially representative embedded benchmark suite. In Proceedings of the fourth annual IEEE international workshop on workload characterization. WWC-4 (Cat. No. 01EX538). IEEE, 3–14.Google ScholarGoogle Scholar
  7. Müller et al.2013. Ferroelectric hafnium oxide: A CMOS-compatible and highly scalable approach to future ferroelectric memories. In 2013 IEEE International Electron Devices Meeting. IEEE, 10–8.Google ScholarGoogle Scholar
  8. S. Kim, R. Vyas, J. Bito, K. Niotaki, A. Collado, A. Georgiadis, and M. M Tentzeris. 2014. Ambient RF energy-harvesting technologies for self-sustainable standalone wireless sensor platforms. Proc. IEEE 102, 11 (2014), 1649–1666.Google ScholarGoogle ScholarCross RefCross Ref
  9. X. Lin, Y. Wang, N. Chang, and M. Pedram. 2016. Concurrent task scheduling and dynamic voltage and frequency scaling in a real-time embedded system with energy harvesting. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 35, 11(2016), 1890–1902.Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. Real Time Engineers Ltd.2021. FreeRTOS Repository. https://github.com/FreeRTOS/FreeRTOS. https://github.com/FreeRTOS/FreeRTOSGoogle ScholarGoogle Scholar
  11. B. Ransford, J. Sorber, and K.Fu. 2011. Mementos: System support for long-running computation on RFID-scale devices. In Proceedings of the sixteenth international conference on Architectural support for programming languages and operating systems. 159–170.Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. E. Ruppel and B. Lucia. 2019. Transactional concurrency control for intermittent, energy-harvesting computing systems. In Proceedings of the 40th ACM SIGPLAN Conference on Programming Language Design and Implementation. 1085–1100.Google ScholarGoogle Scholar

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  • Published in

    cover image ACM Conferences
    ISLPED '22: Proceedings of the ACM/IEEE International Symposium on Low Power Electronics and Design
    August 2022
    192 pages
    ISBN:9781450393546
    DOI:10.1145/3531437

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    • Published: 1 August 2022

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