skip to main content
research-article

Reconfigurable Framework for Environmentally Adaptive Resilience in Hybrid Space Systems

Published:16 July 2020Publication History
Skip Abstract Section

Abstract

Due to ongoing innovations in both sensor technology and spacecraft autonomy, onboard space processing continues to be outpaced by the escalating computational demands required for next-generation missions. Commercial-off-the-shelf, hybrid system-on-chips, combining fixed-logic CPUs with reconfigurable-logic FPGAs, present numerous architectural advantages that address onboard computing challenges. However, commercial devices are highly susceptible to space radiation and require dependable computing strategies to mitigate radiation-induced single-event effects. Depending upon the mission, the dynamics of the near-Earth space-radiation environment expose spacecraft to radiation fluxes that can vary by several orders of magnitude. By adopting an adaptive approach to dependable computing, spacecraft computers can reconfigure system resources to efficiently accommodate changing environmental conditions to maximize system performance while satisfying availability constraints throughout the mission. In this article, we propose Hybrid, Adaptive, Reconfigurable Fault Tolerance (HARFT), a reconfigurable framework for environmentally adaptive resilience in hybrid space systems. Furthermore, we describe a methodology to model adaptive systems, represented as phased-mission systems using Markov chains, subject to the near-Earth space-radiation environment, using a combination of orbital perturbation, geomagnetic field, and single-event effect rate prediction tools. We apply this methodology to evaluate the HARFT architecture using various static and adaptive strategies for several orbital case studies and demonstrate the achievable performability gains.

References

  1. Francesco Abate, Luca Sterpone, Carlos A. Lisboa, Luigi Carro, and Massimo Violante. 2009. New techniques for improving the performance of the lockstep architecture for SEEs mitigation in FPGA embedded processors. IEEE Transactions on Nuclear Science 56, 4 (Aug. 2009), 1992--2000. DOI:https://doi.org/10.1109/TNS.2009.2013237Google ScholarGoogle ScholarCross RefCross Ref
  2. Dimitris Agiakatsikas, Nguyen T. H. Nguyen, Zhuoran Zhao, Tong Wu, Ediz Cetin, Oliver Diessel, and Lingkan Gong. 2016. Reconfiguration control networks for TMR systems with module-based recovery. In Proceedings of the 2016 IEEE 24th Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM’16). 88--91. DOI:https://doi.org/10.1109/FCCM.2016.30Google ScholarGoogle ScholarCross RefCross Ref
  3. Mansoor Alam and Ubaid M. Al-Saggaf. 1986. Quantitative reliability evaluation of repairable phased-mission systems using Markov approach. IEEE Transactions on Reliability 35, 5 (Dec. 1986), 498--503. DOI:https://doi.org/10.1109/TR.1986.4335529Google ScholarGoogle ScholarCross RefCross Ref
  4. Melanie Berg, Christian Poivey, David Petrick, Daniel Espinosa, Austin Lesea, Kenneth A. LaBel, Mark Friendlich, Hak Kim, and Anthony Phan. 2008. Effectiveness of internal versus external SEU scrubbing mitigation strategies in a Xilinx FPGA: Design, test, and analysis. IEEE Transactions on Nuclear Science 55, 4 (Aug. 2008), 2259--2266. DOI:https://doi.org/10.1109/TNS.2008.2001422Google ScholarGoogle ScholarCross RefCross Ref
  5. Cristiana Bolchini, Antonio Miele, and Marco D. Santambrogio. 2007. TMR and partial dynamic reconfiguration to mitigate SEU faults in FPGAs. In Proceedings of the 22nd IEEE International Symposium on Defect and Fault-Tolerance in VLSI Systems (DFT’07). 87--95. DOI:https://doi.org/10.1109/DFT.2007.25Google ScholarGoogle Scholar
  6. Sébastien Bourdarie and Michael Xapsos. 2008. The near-earth space radiation environment. IEEE Transactions on Nuclear Science 55, 4 (Aug. 2008), 1810--1832. DOI:https://doi.org/10.1109/TNS.2008.2001409Google ScholarGoogle ScholarCross RefCross Ref
  7. Matthew J. Cannon, Andrew M. Keller, Hayden C. Rowberry, Corbin A. Thurlow, Andés Pérez-Celis, and Michael J. Wirthlin. 2019. Strategies for removing common mode failures from TMR designs deployed on SRAM FPGAs. IEEE Transactions on Nuclear Science 66, 1 (Jan. 2019), 207--215. DOI:https://doi.org/10.1109/TNS.2018.2877579Google ScholarGoogle ScholarCross RefCross Ref
  8. BAA DARPA. 2018. Blackjack (BAA HR001118S0032). DARPA.Google ScholarGoogle Scholar
  9. BAA DARPA. 2019. Blackjack Pit Boss (BAA HR001119S0012). DARPA.Google ScholarGoogle Scholar
  10. Bill Doncaster, Caleb Williams, and Stephanie DelPozzo. 2019. 2019 Nano/Microsatellite Market Forecast, 9th Edition. SpaceWorks Enterprises, Inc.Google ScholarGoogle Scholar
  11. Larry D. Edmonds. 2000. Proton SEU cross sections derived from heavy-ion test data. IEEE Transactions on Nuclear Science 47, 5 (Oct. 2000), 1713--1728. DOI:https://doi.org/10.1109/23.890997Google ScholarGoogle ScholarCross RefCross Ref
  12. Alan D. George and Christopher M. Wilson. 2018. Onboard processing with hybrid and reconfigurable computing on small satellites. Proceedings of the IEEE 106, 3 (March 2018), 458--470. DOI:https://doi.org/10.1109/JPROC.2018.2802438Google ScholarGoogle ScholarCross RefCross Ref
  13. Robért Glein, Florian Rittner, and Albert Heuberger. 2018. Adaptive single-event effect mitigation for dependable processing systems based on FPGAs. Microprocessors and Microsystems 59 (2018), 46--56. DOI:https://doi.org/10.1016/j.micpro.2018.03.004Google ScholarGoogle ScholarCross RefCross Ref
  14. James R. Heirtzler. 2002. The future of the South Atlantic anomaly and implications for radiation damage in space. Journal of Atmospheric and Solar-Terrestrial Physics 64, 16 (2002), 1701--1708. DOI:https://doi.org/10.1016/S1364-6826(02)00120-7Google ScholarGoogle ScholarCross RefCross Ref
  15. Felix R. Hoots and Ronald L. Roehrich. 1980. Models for Propagation of NORAD Element Sets. Technical Report. Aerospace Defense Command Peterson AFB Co Office of Astrodynamics.Google ScholarGoogle Scholar
  16. Adam Jacobs, Grzegorz Cieslewski, Alan D. George, Ann Gordon-Ross, and Herman Lam. 2012. Reconfigurable fault tolerance: A comprehensive framework for reliable and adaptive FPGA-based space computing. ACM Transactions on Reconfigurable Technology and Systems 5, 4 (Dec. 2012), Article 21, 30 pages. DOI:https://doi.org/10.1145/2392616.2392619Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. Jonathan M. Johnson and Michael J. Wirthlin. 2010. Voter insertion algorithms for FPGA designs using triple modular redundancy. In Proceedings of the 18th Annual ACM/SIGDA International Symposium on Field Programmable Gate Arrays (FPGA’10). ACM, New York, NY, 249--258. DOI:https://doi.org/10.1145/1723112.1723154Google ScholarGoogle Scholar
  18. Josef Koller, Geoffrey D. Reeves, and Reiner H. W. Friedel. 2009. LANL* V1.0: A radiation belt drift shell model suitable for real-time and reanalysis applications. Geoscientific Model Development 2, 2 (2009), 113--122. DOI:https://doi.org/10.5194/gmd-2-113-2009Google ScholarGoogle ScholarCross RefCross Ref
  19. Israel Koren and C. Mani Krishna. 2007. Fault-Tolerant Systems. Morgan Kaufmann, San Francisco, CA.Google ScholarGoogle Scholar
  20. Kuang-Hua Huang and Jacob A. Abraham. 1984. Algorithm-based fault tolerance for matrix operations. IEEE Transactions on Computers C-33, 6 (June 1984), 518--528. DOI:https://doi.org/10.1109/TC.1984.1676475Google ScholarGoogle Scholar
  21. Kenneth A. LaBel and Jonathan A. Pellish. 2014. National Radiation Hardness Assurance (RHA) Planning for NASA Missions: Updated Guidance. NASA Electronic Parts and Packaging Program (NEPP).Google ScholarGoogle Scholar
  22. Robert Le. 2012. Soft Error Mitigation Using Prioritized Essential Bits. Xilinx XAPP538 (v1. 0). Xilinx.Google ScholarGoogle Scholar
  23. David S. Lee, Gregory R. Allen, Gary Swift, Matthew Cannon, Michael Wirthlin, Jeffrey S. George, Rokutaro Koga, and Kangsen Huey. 2015. Single-event characterization of the 20 nm Xilinx Kintex UltraScale field-programmable gate array under heavy ion irradiation. In Proceedings of the 2015 IEEE Radiation Effects Data Workshop (REDW’15). 1--6. DOI:https://doi.org/10.1109/REDW.2015.7336736Google ScholarGoogle ScholarCross RefCross Ref
  24. David S. Lee, Michael King, William Evans, Matthew Cannon, Andrés Pérez-Celis, Jordan Anderson, Michael Wirthlin, and William Rice. 2018. Single-event characterization of 16 nm FinFET Xilinx UltraScale+ devices with heavy ion and neutron irradiation. In Proceedings of the 2018 IEEE Nuclear Space Radiation Effects Conference (NSREC’18). 1--8. DOI:https://doi.org/10.1109/NSREC.2018.8584313Google ScholarGoogle ScholarCross RefCross Ref
  25. David S. Lee, Michael Wirthlin, Gary Swift, and Anthony C. Le. 2014. Single-event characterization of the 28 nm Xilinx Kintex-7 field-programmable gate array under heavy ion irradiation. In Proceedings of the 2014 IEEE Radiation Effects Data Workshop (REDW’14). 1--5. DOI:https://doi.org/10.1109/REDW.2014.7004595Google ScholarGoogle ScholarCross RefCross Ref
  26. Ganghee Lee, Dimitris Agiakatsikas, Tong Wu, Ediz Cetin, and Oliver Diessel. 2017. TLegUp: A TMR code generation tool for SRAM-based FPGA applications using HLS. In Proceedings of the 2017 IEEE 25th Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM’17). 129--132. DOI:https://doi.org/10.1109/FCCM.2017.57Google ScholarGoogle ScholarCross RefCross Ref
  27. Tyler M. Lovelly, Donavon Bryan, Kevin Cheng, Rachel Kreynin, Alan D. George, Ann Gordon-Ross, and Gabriel Mounce. 2014. A framework to analyze processor architectures for next-generation on-board space computing. In Proceedings of the 2014 IEEE Aerospace Conference. 1--10. DOI:https://doi.org/10.1109/AERO.2014.6836387Google ScholarGoogle ScholarCross RefCross Ref
  28. Mischa Möstl, Alexander Dörflinger, Mark Albers, Harald Michalik, and Rolf Ernst. 2019. Self-adaptation for availability in CPU-FPGA systems under soft errors. In Proceedings of the 2019 NASA/ESA Conference on Adaptive Hardware and Systems (AHS’19). 9--16. DOI:https://doi.org/10.1109/AHS.2019.000-6Google ScholarGoogle ScholarCross RefCross Ref
  29. Shubhendu S. Mukherjee, Christopher Weaver, Joel Emer, Steven K. Reinhardt, and Todd Austin. 2003. A systematic methodology to compute the architectural vulnerability factors for a high-performance microprocessor. In Proceedings of the 2003 36th Annual IEEE/ACM International Symposium on Microarchitecture (MICRO-36). 29--40. DOI:https://doi.org/10.1109/MICRO.2003.1253181Google ScholarGoogle ScholarCross RefCross Ref
  30. National Academies of Sciences, Engineering, and Medicine. 2016. Achieving Science with CubeSats: Thinking Inside the Box. National Academies Press, Washington, DC. DOI:https://doi.org/10.17226/23503Google ScholarGoogle Scholar
  31. National Academies of Sciences, Engineering, and Medicine. 2018. Testing at the Speed of Light: The State of U.S. Electronic Parts Space Radiation Testing Infrastructure. National Academies Press, Washington, DC. DOI:https://doi.org/10.17226/24993Google ScholarGoogle Scholar
  32. National Academies of Sciences, Engineering, and Medicine. 2018. Thriving on Our Changing Planet: A Decadal Strategy for Earth Observation from Space. National Academies Press, Washington, DC. DOI:https://doi.org/10.17226/24938Google ScholarGoogle Scholar
  33. Paul P. O’Brien and Sébastien Bourdarie. 2012. The IRBEM library -- open source tools for radiation belt modeling. In Proceedings of the 2012 Fall Meeting of the American Geophysical Union. Article IN53C-1760.Google ScholarGoogle Scholar
  34. Björn Osterloh, Harald Michalik, Sandi A. Habinc, and Björ Fiethe. 2009. Dynamic partial reconfiguration in space applications. In Proceedings of the 2009 NASA/ESA Conference on Adaptive Hardware and Systems. 336--343. DOI:https://doi.org/10.1109/AHS.2009.13Google ScholarGoogle ScholarDigital LibraryDigital Library
  35. Jason A. Poovey, Thomas M. Conte, Markus Levy, and Shay Gal-On. 2009. A benchmark characterization of the EEMBC benchmark suite. IEEE Micro 29, 5 (Sept. 2009), 18--29. DOI:https://doi.org/10.1109/MM.2009.74Google ScholarGoogle ScholarDigital LibraryDigital Library
  36. Paul Pukite and Jan Pukite. 1998. Modeling for Reliability Analysis: Markov Modeling for Reliability, Maintainability, Safety, and Supportability Analyses of Complex Systems. IEEE Press, Piscataway, NJ.Google ScholarGoogle Scholar
  37. Heather Quinn, Tom Fairbanks, Justin L. Tripp, George Duran, and Beatrice Lopez. 2014. Single-event effects in low-cost, low-power microprocessors. In Proceedings of the 2014 IEEE Radiation Effects Data Workshop (REDW’14). 1--9. DOI:https://doi.org/10.1109/REDW.2014.7004596Google ScholarGoogle ScholarCross RefCross Ref
  38. Daniel Sabogal and Alan D. George. 2018. Towards resilient spaceflight systems with virtualization. In Proceedings of the 2018 IEEE Aerospace Conference. 1--8. DOI:https://doi.org/10.1109/AERO.2018.8396689Google ScholarGoogle ScholarCross RefCross Ref
  39. Sebastian Sabogal, Patrick Gauvin, Brad Shea, Daniel Sabogal, Antony Gillette, Christopher Wilson, Ansel Barchowsky, Alan D. George, Gary Crum, and Thomas Flatley. 2017. SSIVP: Spacecraft supercomputing experiment for STP-H6. In Proceedings of the 31st Annual AIAA/USU Conference on Small Satellites. 1--12.Google ScholarGoogle Scholar
  40. Aitzan Sari and Mihalis Psarakis. 2011. Scrubbing-based SEU mitigation approach for systems-on-programmable-chips. In Proceedings of the 2011 International Conference on Field-Programmable Technology. 1--8. DOI:https://doi.org/10.1109/FPT.2011.6132703Google ScholarGoogle ScholarCross RefCross Ref
  41. Alex Shye, Joseph Blomstedt, Tipp Moseley, Vijay J. Reddi, and Daniel A. Connors. 2009. PLR: A software approach to transient fault tolerance for multicore architectures. IEEE Transactions on Dependable and Secure Computing 6, 2 (April 2009), 135--148. DOI:https://doi.org/10.1109/TDSC.2008.62Google ScholarGoogle ScholarDigital LibraryDigital Library
  42. Felix Siegle, Tanya Vladimirova, Jørgen Ilstad, and Omar Emam. 2015. Mitigation of radiation effects in SRAM-based FPGAs for space applications. ACM Computing Surveys 47, 2 (Jan. 2015), Article 37, 34 pages. DOI:https://doi.org/10.1145/2671181Google ScholarGoogle ScholarDigital LibraryDigital Library
  43. L. Sterpone and M. Violante. 2006. A new reliability-oriented place and route algorithm for SRAM-based FPGAs. IEEE Transactions on Computers 55, 6 (June 2006), 732--744. DOI:https://doi.org/10.1109/TC.2006.82Google ScholarGoogle ScholarDigital LibraryDigital Library
  44. Aaron Stoddard, Ammon Gruwell, Peter Zabriskie, and Michael J. Wirthlin. 2017. A hybrid approach to FPGA configuration scrubbing. IEEE Transactions on Nuclear Science 64, 1 (Jan. 2017), 497--503. DOI:https://doi.org/10.1109/TNS.2016.2636666Google ScholarGoogle ScholarCross RefCross Ref
  45. Michael A. Swartout. 2017. CubeSats and mission success, 2017 update. In Proceedings of the NASA Electronic Parts and Packaging (NEPP) Electronics Technology Workshop (ETW’17).Google ScholarGoogle Scholar
  46. Lucas A. Tambara, Felipe Almeida, Paolo Rech, Fernanda L. Kastensmidt, Giovanni Bruni, and Christopher Frost. 2015. Measuring failure probability of coarse and fine grain TMR schemes in SRAM-based FPGAs under neutron-induced effects. In Applied Reconfigurable Computing, K. Sano, D. Soudris, M. Hübner, and P. C. Diniz (Eds.). Springer International Publishing, Cham, Switzerland, 331--338.Google ScholarGoogle Scholar
  47. Erwan Thébault, Christopher C. Finlay, Ciarán D. Beggan, Patrick Alken, Julien Aubert, Olivier Barrois, Francois Bertrand, et al. 2015. International geomagnetic reference field: The 12th generation. Earth, Planets and Space 67, 1 (2015), 79.Google ScholarGoogle ScholarCross RefCross Ref
  48. Jorge Tonfat, Fernanda Lima Kastensmidt, Paolo Rech, Ricardo Reis, and Heather M. Quinn. 2015. Analyzing the effectiveness of a frame-level redundancy scrubbing technique for SRAM-based FPGAs. IEEE Transactions on Nuclear Science 62, 6 (Dec. 2015), 3080--3087. DOI:https://doi.org/10.1109/TNS.2015.2489601Google ScholarGoogle ScholarCross RefCross Ref
  49. Nikolai A. Tsyganenko. 1989. A magnetospheric magnetic field model with a warped tail current sheet. Planetary and Space Science 37, 1 (1989), 5--20. DOI:https://doi.org/10.1016/0032-0633(89)90066-4Google ScholarGoogle ScholarCross RefCross Ref
  50. Allan J. Tylka, James H. Adams, Paul R. Boberg, Buddy Brownstein, William F. Dietrich, Erwin O. Flueckiger, Edward L. Petersen, Margaret A. Shea, Don F. Smart, and Edward C. Smith. 1997. CREME96: A revision of the cosmic ray effects on micro-electronics code. IEEE Transactions on Nuclear Science 44, 6 (Dec. 1997), 2150--2160. DOI:https://doi.org/10.1109/23.659030Google ScholarGoogle ScholarCross RefCross Ref
  51. Dazhi Wang and Kishor S. Trivedi. 2007. Reliability analysis of phased-mission system with independent component repairs. IEEE Transactions on Reliability 56, 3 (Sept. 2007), 540--551. DOI:https://doi.org/10.1109/TR.2007.903268Google ScholarGoogle ScholarCross RefCross Ref
  52. Christopher Wilson and Alan D. George. 2018. CSP hybrid space computing. Journal of Aerospace Information Systems 15, 4 (Feb. 2018), 215--227. DOI:https://doi.org/10.2514/1.I010572Google ScholarGoogle ScholarCross RefCross Ref
  53. Christopher Wilson, Sebastian Sabogal, Alan D. George, and Ann Gordon-Ross. 2017. Hybrid, adaptive, and reconfigurable fault tolerance. In Proceedings of the 2017 IEEE Aerospace Conference. 1--11. DOI:https://doi.org/10.1109/AERO.2017.7943867Google ScholarGoogle ScholarCross RefCross Ref
  54. Michael Wirthlin. 2015. High-reliability FPGA-based systems: Space, high-energy physics, and beyond. Proceedings of the IEEE 103, 3 (March 2015), 379--389. DOI:https://doi.org/10.1109/JPROC.2015.2404212Google ScholarGoogle ScholarCross RefCross Ref
  55. Xilinx. 2018. Soft Error Mitigation Controller (v4.1 ed.). Xilinx Product Guide (PG036). Xilinx.Google ScholarGoogle Scholar
  56. Xilinx. 2018. Zynq-7000 SoC Technical Reference Manual (v1.12.2 ed.). Xilinx User Guide (UG585). Xilinx.Google ScholarGoogle Scholar
  57. Xilinx. 2019. Libmetal and OpenAMP for Zynq Devices User Guide (v2019.1 ed.). Xilinx User Guide (UG1186). Xilinx.Google ScholarGoogle Scholar
  58. Xilinx. 2019. Zynq UltraScale+ Device Technical Reference Manual (v1.9 ed.). Xilinx User Guide (UG1085). Xilinx.Google ScholarGoogle Scholar
  59. Hongyan Zhang, Michael A. Kochte, Michael E. Imhof, Lars Bauer, Hans-Joachim Wunderlich, and Jörg Henkel. 2014. GUARD: Guaranteed reliability in dynamically reconfigurable systems. In Proceedings of the 2014 51st ACM/EDAC/IEEE Design Automation Conference (DAC’14). 1--6. DOI:https://doi.org/10.1145/2593069.2593146Google ScholarGoogle ScholarDigital LibraryDigital Library
  60. Zhuoran Zhao, Dimitris Agiakatsikas, Nguyen T. H. Nguyen, Ediz Cetin, and Oliver Diessel. 2016. Fine-grained module-based error recovery in FPGA-based TMR systems. In Proceeedings of the 2016 International Conference on Field-Programmable Technology (FPT’16). 101--108. DOI:https://doi.org/10.1109/FPT.2016.7929433Google ScholarGoogle ScholarCross RefCross Ref

Index Terms

  1. Reconfigurable Framework for Environmentally Adaptive Resilience in Hybrid Space Systems

              Recommendations

              Comments

              Login options

              Check if you have access through your login credentials or your institution to get full access on this article.

              Sign in

              Full Access

              PDF Format

              View or Download as a PDF file.

              PDF

              eReader

              View online with eReader.

              eReader

              HTML Format

              View this article in HTML Format .

              View HTML Format
              About Cookies On This Site

              We use cookies to ensure that we give you the best experience on our website.

              Learn more

              Got it!