实时数字孪生平台：航空自组网核心网选择案例研究
Real-Time Digital Twin Platform: A Case Study on Core Network Selection in Aeronautical Ad-Hoc Networks
AI总结：
针对数字孪生缺乏专用开源实时方案、现有应用依赖离线数据验证有效性不足的问题，本文开发了采用微服务架构、鲁棒数据管道和开源交互界面的实时数字孪生平台，并通过航空自组网核心网选择案例验证其可在数据检索失败时支持实时决策。
摘要：
数字孪生（DT）的发展受限于缺乏能满足动态应用需求的专用开源解决方案，这导致当前最先进的DT应用都使用离线数据进行验证。然而，这种方法未能整合实时数据——而实时性是DT最重要的特性之一，这会降低DT应用在航空自组网（AANETs）等场景中的验证有效性。针对这一问题，我们开发了一个实时数字孪生平台，并以AANETs中的核心网选择为案例进行实现。我们采用基于微服务的架构，设计了鲁棒的数据管道，还使用开源工具开发了交互式用户界面。依托这些设计，该平台可在存在数据检索失败的情况下支持实时决策。
英文摘要：
The development of Digital Twins (DTs) is hindered by a lack of specialized, open-source solutions that can meet the demands of dynamic applications. This has caused state-of-the-art DT applications to be validated using offline data. However, this approach falls short of integrating real-time data, which is one of the most important characteristics of DTs. This can limit the validating effectiveness of DT applications in cases such as aeronautical ad-hoc networks (AANETs). Considering this, we develop a Real-Time Digital Twin Platform and implement core network selection in AANETs as a case study. In this, we implement microservice-based architecture and design a robust data pipeline. Additionally, we develop an interactive user interface using open-source tools. Using this, the platform supports real-time decision-making in the presence of data retrieval failures.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
