Graduation Semester and Year

Spring 2025

Language

English

Document Type

Thesis

Degree Name

Master of Science in Computer Science

Department

Computer Science and Engineering

First Advisor

Jiayi Meng

Abstract

The Nvidia Aerial Omniverse Digital Twin (AODT) platform provides a comprehensive framework for modeling radio network behavior under varying user mobility scenarios for 5G, 6G, and beyond. However, the current AODT implementation relies on a graphical user interface (GUI) to manually configure simulation parameters and initiate runs, which limits its capability to support automated, large-scale simulations that are needed by future cellular networks. In this study, we re-architect AODT to enable automation and control through scripts by decoupling its original simulation backend engine from the GUI. We adopt a client-server architecture, where the server runs the simulation backend engine controlled by client-side scripts. The client can pass custom user mobility and radio configurations to the server—completely bypassing the original UI layer. This re-architected system enhances AODT’s automation, scalability, and integration with third-party systems by supporting script-driven simulations. Its modular and adaptable design can support diverse research and operational scenarios, e.g., real-time simulations of digital twins. This work represents a significant advancement toward more configurable and automated simulation environments for digital twin platforms.

Keywords

Aerial, Nvidia, Digital Twins, 5G, 6G, Network, Simulations

Disciplines

Other Computer Sciences | Systems Architecture

License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.

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