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：针对以中继为中心的分布式卫星系统（DSS），我们提出了一种集成的多端口并发通信可分负载理论（MPCC-DLT）框架，该框架能够捕获在异构星上处理与星间链路条件下的并发数据分发、并行计算及结果回传过程。我们提出了一种公式化方法，可得到最优负载分配与完成时间的闭合表达式，明确量化了计算速度、链路带宽及结果量开销的联合影响。进一步推导出截止时间可行性条件，实现对满足时间关键任务需求的协作卫星集群规模的显式规划。大量仿真结果表明：高度可分解任务可显著降低延迟，而通信密集型任务因结果传输开销而呈现收益递减效应。为衔接理论与实际应用，我们在MPCC-DLT框架中扩展了实时准入控制机制，能够处理随机任务到达与截止时间约束，实现阻塞感知运行。实时仿真揭示了任务结构与系统参数如何共同支配截止时间满足率与运行状态。总体而言，本研究首次为分布式卫星系统建立了可解析处理的MPCC-DLT模型，并为面向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指导。