# Carbon-Aware Orchestration of Integrated Satellite Aerial Terrestrial Networks via Digital Twin

arXiv: https://arxiv.org/abs/2510.17825 · HTML: https://mlsanity.com/paper/2510.17825/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 4 of its 15 references that are in the map.
- First posted on arXiv 1 Oct 2025.

## Builds on (most cited first, 4 of 4)

- [Leveraging Large Language Models for Integrated Satellite-Aerial-Terrestrial Networks: Recent Advances and Future Directions](https://mlsanity.com/paper/2407.04581/) (2024)
- [Digital Twins based Day-ahead Integrated Energy System Scheduling under Load and Renewable Energy Uncertainties](https://mlsanity.com/paper/2109.14423/) (2021)
- [Integrating Terrestrial and Non-terrestrial Networks: 3D Opportunities and Challenges](https://mlsanity.com/paper/2207.10385/) (2022)
- [EASE: Energy-Aware Job Scheduling for Vehicular Edge Networks With Renewable Energy Resources](https://mlsanity.com/paper/2111.02186/) (2021)

## Abstract (arXiv)

Integrated Satellite Aerial Terrestrial Networks (ISATNs) are envisioned as key enablers of 6G, providing global connectivity for applications such as autonomous transportation, Industrial IoT, and disaster response. Their large-scale deployment, however, risks unsustainable energy use and carbon emissions. This work advances prior energy-aware studies by proposing a carbon-aware orchestration framework for ISATNs that leverages Digital Twin (DT) technology. The framework adopts grams of CO2-equivalent per bit (gCO2/bit) as a primary sustainability metric and implements a multi timescale Plan Do Check Act (PDCA) loop that combines day-ahead forecasting with real-time adaptive optimization. ISATN-specific control knobs, including carbon-aware handovers, UAV duty cycling, and renewable-aware edge placement, are exploited to reduce emissions. Simulation results with real carbon intensity data show up to 29% lower gCO2/bit than QoS-only orchestration, while improving renewable utilization and resilience under adverse events.