A Multi-Port Concurrent Communication Model for handling Compute Intensive Tasks on Distributed Satellite System Constellations

2026-01-03

arXiv.org

AI Summary

This study addresses the challenge of collaborative scheduling and real-time guarantee for compute-intensive tasks in distributed satellite systems, where heterogeneous on-board processing capabilities and dynamic inter-satellite links complicate execution. The authors propose a Multi-Port Concurrent Communication Divisible Load Theory (MPCC-DLT) framework that unifies the modeling of data distribution, parallel computation, and result collection. They formulate the first analytically tractable MPCC-DLT model, deriving closed-form solutions for optimal load allocation and makespan, along with a condition to determine the minimum number of collaborating satellites required to meet a given deadline. Integrating real-time admission control with a blocking-aware scheduling mechanism, simulations demonstrate that the proposed approach significantly reduces execution latency for highly divisible tasks, offering both theoretical foundations and practical guidance for application-aware scheduling and system design in future satellite constellations.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization
• Search and Optimization: Distributed Search

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Federated Web and WoT systems, including distributed, federated and edge-based data processing
• Economics, Online Markets and Human Computation: Cost models of using LLMs in production systems
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

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.

Problem

• Distributed Satellite Systems
• Compute Intensive Tasks
• Concurrent Communication
• Deadline Constraints
• Divisible Load Theory

Innovation

• Multi-Port Concurrent Communication
• Divisible Load Theory
• Distributed Satellite Systems
• Deadline Feasibility
• Real-time Admission Control