We develop an integrated Multi-Port Concurrent Communication Divisible Load Theory (MPCC-DLT) framework for relay-centric distributed satellite systems (DSS), capturing concurrent data dissemination, parallel computation, and result return under heterogeneous onboard processing and inter-satellite link conditions. We propose a formulation that yields closed-form expressions for optimal load allocation and completion time that explicitly quantify the joint impact of computation speed, link bandwidth, and result-size overhead. We further derive deadline feasibility conditions that enable explicit sizing of cooperative satellite clusters to meet time-critical task requirements. Extensive simulation results demonstrate that highly distributable tasks achieve substantial latency reduction, while communication-heavy tasks exhibit diminishing returns due to result-transfer overheads. To bridge theory and practice, we extend the MPCC-DLT framework with a real-time admission control mechanism that handles stochastic task arrivals and deadline constraints, enabling blocking-aware operation. Our real-time simulations illustrate how task structure and system parameters jointly govern deadline satisfaction and operating regimes. Overall, this work provides the first analytically tractable MPCC-DLT model for distributed satellite systems and offers actionable insights for application-aware scheduling and system-level design of future satellite constellations.

翻译：本文为以中继为中心的分布式卫星系统开发了一个集成的多端口并发通信可分割负载理论框架，该框架能够捕捉异构星载处理能力和星间链路条件下的并发数据分发、并行计算与结果返回过程。我们提出了一种数学表述，推导出最优负载分配与完成时间的闭式表达式，显式量化了计算速度、链路带宽和结果规模开销的联合影响。进一步推导出截止时间可行性条件，为满足时间关键型任务需求提供了协同卫星集群规模的显式确定方法。大量仿真结果表明：高度可分布的任务能实现显著的延迟降低，而通信密集型任务因结果传输开销存在收益递减现象。为衔接理论与实际，我们扩展了MPCC-DLT框架，引入实时准入控制机制以处理随机任务到达和截止时间约束，实现阻塞感知操作。实时仿真揭示了任务结构与系统参数如何共同决定截止时间满足率及运行状态。总体而言，本研究首次提出了适用于分布式卫星系统的可解析处理MPCC-DLT模型，为未来卫星星座的应用感知调度与系统级设计提供了可操作的见解。