混合空间系统环境适应弹性的可重构框架

Sebastian Sabogal, A. George, Christopher M. Wilson
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引用次数: 9

摘要

由于传感器技术和航天器自主性的不断创新,机载空间处理继续被下一代任务所需的不断升级的计算需求所超越。商用现成的混合片上系统,结合了固定逻辑的cpu和可重构逻辑的fpga,提供了许多架构优势,解决了板载计算的挑战。然而,商用设备极易受到空间辐射的影响,需要可靠的计算策略来减轻辐射引起的单事件效应。根据任务的不同,近地空间辐射环境的动力学使航天器暴露在可能变化几个数量级的辐射通量中。通过采用可靠计算的自适应方法,航天器计算机可以重新配置系统资源,以有效地适应不断变化的环境条件,从而最大化系统性能,同时满足整个任务的可用性约束。在本文中,我们提出了混合,自适应,可重构容错(HARFT),这是一种用于混合空间系统环境适应弹性的可重构框架。此外,我们描述了一种方法来建模自适应系统,表示为阶段任务系统,使用马尔可夫链,受近地空间辐射环境,结合轨道扰动,地磁场和单事件效应率预测工具。我们将此方法应用于几个轨道案例研究中,使用各种静态和自适应策略来评估HARFT架构,并展示了可实现的性能增益。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Reconfigurable Framework for Environmentally Adaptive Resilience in Hybrid Space Systems
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.
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