Digital twin platform for real-time data communication in UAV environment

IF 6.2 2区 计算机科学 Q1 COMPUTER SCIENCE, THEORY & METHODS
Changhui Bae , Euteum Choi , Sungjoo Kang , Sungsoo Ahn , Seongjin Lee
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引用次数: 0

Abstract

Real-time data communication is essential for controlling objects from virtual space to physical space through digital twins. However, existing digital twin platforms for UAV environments primarily focus on data modeling, prediction, and simulation rather than real-time performance and have not been extensively evaluated for real-time data communication, which may limit their applicability in real-world UAV operations. This paper introduces the RC-DT(Real-Time Communication Digital Twin)-Platform, which supports real-time data communication in UAV environments. The RC-DT-Platform’s data communication performance was evaluated by measuring the throughput as bandwidth, and the number of registered items increased. Results show that the RC-DT-Platform can transmit approximately 454 data/sec for 100 bytes data, 119 data/sec for 100 KB data, and 0.7 data/sec for 16 MB of data. Additionally, with 32 registered objects, the RC-DT-Platform can achieve a read throughput of about 3500 data/sec, regardless of data size. The performance of pure Ditto degrades by up to approximately 10 times as the number of registered objects increases up to 32, whereas the RC-DT-Platform maintains a degradation of less than 6.25 times. Thus, the RC-DT-Platform meets the required real-time data communication performance by considering flight speed, data size, and data generation rate.
无人机环境下实时数据通信的数字孪生平台
实时数据通信是通过数字孪生控制对象从虚拟空间到物理空间的关键。然而,用于无人机环境的现有数字孪生平台主要侧重于数据建模、预测和仿真,而不是实时性能,并且尚未对实时数据通信进行广泛评估,这可能限制它们在实际无人机操作中的适用性。介绍了实时通信数字孪生(RC-DT)平台,该平台支持无人机环境下的实时数据通信。通过测量吞吐量作为带宽来评估rc - dt平台的数据通信性能,并且注册项目数量增加。结果表明,rc - dt平台对100字节数据的传输速度约为454数据/秒,对100 KB数据的传输速度约为119数据/秒,对16 MB数据的传输速度约为0.7数据/秒。此外,在32个注册对象的情况下,无论数据大小如何,rc - dt平台都可以实现约3500数据/秒的读取吞吐量。当注册对象的数量增加到32时,纯Ditto的性能下降了大约10倍,而rc - dt平台的性能下降不到6.25倍。因此,rc - dt平台通过考虑飞行速度、数据大小和数据生成速率来满足所需的实时数据通信性能。
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来源期刊
CiteScore
19.90
自引率
2.70%
发文量
376
审稿时长
10.6 months
期刊介绍: Computing infrastructures and systems are constantly evolving, resulting in increasingly complex and collaborative scientific applications. To cope with these advancements, there is a growing need for collaborative tools that can effectively map, control, and execute these applications. Furthermore, with the explosion of Big Data, there is a requirement for innovative methods and infrastructures to collect, analyze, and derive meaningful insights from the vast amount of data generated. This necessitates the integration of computational and storage capabilities, databases, sensors, and human collaboration. Future Generation Computer Systems aims to pioneer advancements in distributed systems, collaborative environments, high-performance computing, and Big Data analytics. It strives to stay at the forefront of developments in grids, clouds, and the Internet of Things (IoT) to effectively address the challenges posed by these wide-area, fully distributed sensing and computing systems.
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