Reconfigurable Framework for Environmentally Adaptive Resilience in Hybrid Space Systems

Author:

Sabogal Sebastian1,George Alan1,Wilson Christopher2

Affiliation:

1. University of Pittsburgh, Pittsburgh, PA

2. NASA Goddard Space Flight Center, Greenbelt, MD

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.

Funder

IUCRC Program of the National Science Foundation

SHREC industry and agency members

Publisher

Association for Computing Machinery (ACM)

Subject

General Computer Science

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