Spacecraft increasingly rely on heterogeneous computing resources spanning onboard flight computers, orbital data centers, ground station edge nodes, and terrestrial cloud infrastructure. Selecting where a workload should execute is a nontrivial multi objective problem driven by latency, reliability, power, communication constraints, cost, and regulatory feasibility. This paper introduces a quantitative optimization framework that formalizes compute location selection through empirically measurable metrics, normalized scoring, feasibility constraints, and a unified utility function designed to operate under incomplete information. We evaluate the model on two representative workloads demonstrating how the framework compares compute tiers and identifies preferred deployment locations. The approach provides a structured, extensible method for mission designers to reason about compute placement in emerging space architectures.

翻译：航天器日益依赖异构计算资源，这些资源涵盖星载飞行计算机、轨道数据中心、地面站边缘节点以及地面云基础设施。选择工作负载应在何处执行是一个复杂的多目标优化问题，其决策受延迟、可靠性、功耗、通信约束、成本及法规可行性等多重因素驱动。本文提出一种定量优化框架，通过经验可测指标、归一化评分、可行性约束以及专为不完全信息环境设计的统一效用函数，将计算位置选择问题形式化。我们通过两个代表性工作负载对该模型进行评估，展示了该框架如何比较不同计算层级并确定优选部署位置。该方法为任务设计者提供了一种结构化、可扩展的途径，以推演新兴空间架构中的计算布局策略。