Performance Evaluation of Integrated Hard Real-Time Application and RISC V Processor for Spacecraft on Board Software Application

Authors

Keywords:

Space/Avionics, Onboard software system, Baremetal Cyclic executives, RTOS, Multiprocessor, Hard Real Time Systems, RISC V, Closed Loop systems

Abstract

Space industries operating critical missions and safety aspects must operate robust and error-free software systems. A trace amount of error causes failure of the entire spacecraft system; hence, the onboard software of spacecraft systems typically uses Baremetal Cyclic executives to maintain robustness under error-free conditions. Baremetal Cyclic executive software programs are highly predictable in their behavior, and have been evaluated and proven critically for space applications. Technology advent with increased computational power and concurrency necessitates high-end applications of spacecraft systems such as Agriculture, Weather forecasting, communication, and geospatial applications. To meet these challenges, spacecraft systems must be upgraded to handle high-level computational loads, time complexities, and parallelism in activity at the manifold. Currently, space agencies across the globe replace the conventional Baremetal Cyclic executives with advanced RTOS developed on single/multicore processors such as Power PC and LEON4 based on ARINC 653 specifications, which are proprietary, run with the operating system, that is, VxWorks, RTEMS, etc. The execution of the RISC V architecture in the onboard software of a spacecraft system offers advantages, such as openness, modularity, extensibility, and stability. Many RISC-V designs have single/multicore architectures with open-source RTOS support. In the present work, we developed a prototype built on hard real-time satellite application software and evaluated its performance using an RTOS stack on a RISC V series. This research also developed a library to allow portable application development for any flavor of the RISC V architecture.

Downloads

Download data is not yet available.

References

L. E. Rubio-Anguiano, J. L. Briz and A. Ramírez-Treviño, "Accounting for Preemption and Migration Costs in the Calculation of Hard Real-Time Cyclic Executives for MPSoCs," in IEEE Robotics and Automation Letters, vol. 7, no. 3, pp. 7990-7997, July 2022, doi: 10.1109/LRA.2022.3186489.

D. Palmer and R. S. Holmes, “Extremely Low Resource Optical Identifier: A License Plate for Your Satellite,” Journal of Spacecraft and Rockets, vol. 55, no. 4, pp. 1014–1023, Jul. 2018, doi: 10.2514/1.a34106.

M. B. Quadrelli et al., “Guidance, Navigation, and Control Technology Assessment for Future Planetary Science Missions,” Journal of Guidance Control and Dynamics, vol. 38, no. 7, pp. 1165–1186, Jul. 2015, doi: 10.2514/1.g000525.

G. Lentaris et al., “High-Performance Embedded Computing in Space: Evaluation of Platforms for Vision-Based Navigation,” Journal of Aerospace Information Systems, vol. 15, no. 4, pp. 178–192, Apr. 2018, doi: 10.2514/1.i010555.

N. -J. Wessman et al., "De-RISC: the First RISC-V Space-Grade Platform for Safety-Critical Systems," 2021 IEEE Space Computing Conference (SCC), Laurel, MD, USA, 2021, pp. 17-26, doi: 10.1109/SCC49971.2021.00010.

N. -J. Wessman et al., "De-RISC: A Complete RISC-V Based Space-Grade Platform," 2022 Design, Automation & Test in Europe Conference & Exhibition (DATE), Antwerp, Belgium, 2022, pp. 802-807, doi: 10.23919/DATE54114.2022.9774557.

L. A. Aranda et al., “Analysis of the Critical Bits of a RISC-V Processor Implemented in an SRAM-Based FPGA for Space Applications,” Electronics, vol. 9, no. 1, p. 175, Jan. 2020, doi: 10.3390/electronics9010175.

C. Villalpando, D. Rennels, R. Some and M. Cabanas-Holmen, "Reliable multicore processors for NASA space missions," 2011 Aerospace Conference, Big Sky, MT, USA, 2011, pp. 1-12, doi: 10.1109/AERO.2011.5747447.

B. Bornstein, T. Estlin, B. Clement and P. Springer, "Using a multicore processor for rover autonomous science," 2011 Aerospace Conference, Big Sky, MT, USA, 2011, pp. 1-9, doi: 10.1109/AERO.2011.5747454.

E. A. Omran, W. A. Murtada and A. Serageldin, "Spacecraft on-board real time software architecture for fault detection and identification," 2017 12th International Conference on Computer Engineering and Systems (ICCES), Cairo, Egypt, 2017, pp. 615-620, doi: 10.1109/ICCES.2017.8275379.

F. Bruhn, N. Tsog, F. Kunkel, O. Flordal, and I. A. Troxel, “Enabling radiation tolerant heterogeneous GPU-based onboard data processing in space,” Ceas Space Journal, vol. 12, no. 4, pp. 551–564, Jun. 2020, doi: 10.1007/s12567-020-00321-9.

A. E. Wilson, M. Wirthlin and N. G. Baker, "Neutron Radiation Testing of RISC-V TMR Soft Processors on SRAM-Based FPGAs," in IEEE Transactions on Nuclear Science, vol. 70, no. 4, pp. 603-610, April 2023, doi: 10.1109/TNS.2023.3235582.

S. Tiwari, N. Gala, C. Rebeiro, and V. Kamakoti, “PERI,” ACM Transactions on Architecture and Code Optimization, vol. 18, no. 3, pp. 1–26, Apr. 2021, doi: 10.1145/3446210.

N. Iuga, I. Zagan and V. G. Gaitan, "CPU Execution Time Analysis based on RISC-V ISA Simulators: A Survey," 2022 International Conference on Development and Application Systems (DAS), Suceava, Romania, 2022, pp. 12-18, doi: 10.1109/DAS54948.2022.9786163.

A. Dörflinger et al., “A comparative survey of open-source application-class RISC-V processor implementations,” Proceedings of the 18th ACM International Conference on Computing Frontiers. ACM, May 11, 2021. doi: 10.1145/3457388.3458657.

G. R. Granholm, P. J. Cefola, and W. L. Harris, “Bridging the Tech Gap: Using STEM Internships to Accelerate Innovation in the U.S. Air Force and Space Force,” AIAA SCITECH 2022 Forum. American Institute of Aeronautics and Astronautics, Jan. 03, 2022. doi: 10.2514/6.2022-1998.

S. Abdul Halim, M. H. Othman, A. G. Buja, N. N. Abdul Rahid, A. A. Sharip, and S. M. Md Zain, “C19-SmartQ: Applying Real-Time Multi-Organization Queuing Management System Using Predictive Model to Maintain Social Distancing,” International Journal of Interactive Mobile Technologies (iJIM), vol. 15, no. 06. International Association of Online Engineering (IAOE), p. 108, Mar. 30, 2021. doi: 10.3991/ijim.v15i06.20597.

A. Obukhov, D. Dedov, A. Siukhin, and A. Arkhipov, “Mobile Simulator Control System for Isolating Breathing Apparatus of Software-Hardware Platform”, Int. J. Interact. Mob. Technol., vol. 14, no. 08, pp. pp. 32–42, May 2020.

F. Al Huda, H. Tolle, and R. Andrie Asmara, “Realtime Online Daily Living Activity Recognition Using Head-Mounted Display”, Int. J. Interact. Mob. Technol., vol. 11, no. 3, pp. pp. 67–77, Apr. 2017.

Sharma, R., & Dhabliya, D. (2019). A review of automatic irrigation system through IoT. International Journal of Control and Automation, 12(6 Special Issue), 24-29. Retrieved from www.scopus.com

Ana Rodriguez, Kristinsdóttir María, Pekka Koskinen Pieter van der Meer, Thomas Müller. Machine Learning Techniques for Multi-criteria Decision Making in Decision Science. Kuwait Journal of Machine Learning, 2(4). Retrieved from http://kuwaitjournals.com/index.php/kjml/article/view/214

Downloads

Published

16.07.2023

How to Cite

Y., V. ., Desai, K. ., Upendra, R. S. ., Prasad, V. ., Suvanam, S. B. ., Biradar, A. ., S., S. ., & S., R. . (2023). Performance Evaluation of Integrated Hard Real-Time Application and RISC V Processor for Spacecraft on Board Software Application. International Journal of Intelligent Systems and Applications in Engineering, 11(3), 810–817. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/3287

Issue

Section

Research Article