Resource-Aware Task Allocator Design: Insights and Recommendations for Distributed Satellite Constellations

2026-01-10

arXiv.org

AI Summary

This work addresses real-time task blocking and latency in low- to mid-Earth orbit distributed satellite constellations caused by stringent onboard resource constraints. To this end, the authors propose the Resource-Aware Task Allocator (RATA), a dynamic scheduling framework built upon a single-layer tree network (SLTN) architecture that jointly incorporates real-time satellite resource states, task arrival rates, and eclipse-induced energy–communication coupling constraints. The study presents the first quantitative characterization of the nonlinear relationship between constellation scale and system performance, identifying CPU availability as the primary bottleneck for task blocking and pinpointing the critical threshold at which system performance transitions from gradual degradation to abrupt collapse. Experimental results demonstrate robust energy supply under solar-aware scheduling; however, CPU bottlenecks intensify rapidly with constellation expansion, thereby establishing a practical upper bound on scalable constellation size.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Constraint Satisfaction and Optimization: Satisfiability
• Machine Learning: Scalability of ML Systems

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems
• Search and Retrieval-Augmented AI: Efficiency and scalability of Web search engines

Abstract

We present the design of a Resource-Aware Task Allocator (RATA) and an empirical analysis in handling real-time tasks for processing on Distributed Satellite Systems (DSS). We consider task processing performance across low Earth orbit (LEO) to Low-Medium Earth Orbit (Low-MEO) constellation sizes, under varying traffic loads. Using Single-Level Tree Network(SLTN)-based cooperative task allocation architecture, we attempt to evaluate some key performance metrics - blocking probabilities, response times, energy consumption, and resource utilization across several tens of thousands of tasks per experiment. Our resource-conscious RATA monitors key parameters such as arrival rate, resources (on-board compute, storage, bandwidth, battery) availability, satellite eclipses'influence in processing and communications. This study is an important step towards analyzing the performance under lighter to stress inducing levels of compute intense workloads to test the ultimate performance limits under the combined influence of the above-mentioned factors. Results show pronounced non-linear scaling: while capacity increases with constellation size, blocking and delay grow rapidly, whereas energy remains resilient under solar-aware scheduling. The analysis identifies a practical satellite-count limit for baseline SLTNs and demonstrates that CPU availability, rather than energy, is the primary cause of blocking. These findings provide quantitative guidance by identifying thresholds at which system performance shifts from graceful degradation to collapse.

Problem

• Distributed Satellite Systems
• Task Allocation
• Resource Awareness
• Real-time Tasks
• Constellation Scalability

Innovation

• Resource-Aware Task Allocation
• Distributed Satellite Systems
• Single-Level Tree Network
• Non-linear Scalability
• Eclipse-aware Scheduling