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Article

A Novel Video Transmission Latency Measurement Method for Intelligent Cloud Computing

College of Ocean Information Engineering, Jimei University, Xiamen 361021, China
*
Author to whom correspondence should be addressed.
Appl. Sci. 2022, 12(24), 12884; https://doi.org/10.3390/app122412884
Submission received: 20 October 2022 / Revised: 8 December 2022 / Accepted: 12 December 2022 / Published: 15 December 2022
(This article belongs to the Special Issue Computational Intelligence in Image and Video Analysis)

Abstract

Low latency video transmission is gaining importance in time-critical applications using real-time cloud-based systems. Cloud-based Virtual Reality (VR), remote control, and AI response systems are emerging use cases that demand low latency and good reliability. Although there are many video transmission schemes that claim low latency, they vary over different network conditions. Therefore, it is necessary to develop methods that can accurately measure end-to-end latency online, continuously, without any content modification. This research brings these applications one step closer to addressing these next generation use cases. This paper analyzes the cause of end-to-end latency within a video transmission system, and then proposes three methods to measure the latency: timecode, remote online, and lossless remote video online. The corresponding equipment was designed and implemented. The actual measurement of the three methods using related equipment proved that our proposed method can accurately and effectively measure the end-to-end latency of the video transmission system.
Keywords: real-time video; timecode; remote online; lossless remote video online real-time video; timecode; remote online; lossless remote video online

Share and Cite

MDPI and ACS Style

Wu, Y.; Bai, X.; Hu, Y.; Chen, M. A Novel Video Transmission Latency Measurement Method for Intelligent Cloud Computing. Appl. Sci. 2022, 12, 12884. https://doi.org/10.3390/app122412884

AMA Style

Wu Y, Bai X, Hu Y, Chen M. A Novel Video Transmission Latency Measurement Method for Intelligent Cloud Computing. Applied Sciences. 2022; 12(24):12884. https://doi.org/10.3390/app122412884

Chicago/Turabian Style

Wu, Yiliang, Xue Bai, Yendo Hu, and Minghong Chen. 2022. "A Novel Video Transmission Latency Measurement Method for Intelligent Cloud Computing" Applied Sciences 12, no. 24: 12884. https://doi.org/10.3390/app122412884

APA Style

Wu, Y., Bai, X., Hu, Y., & Chen, M. (2022). A Novel Video Transmission Latency Measurement Method for Intelligent Cloud Computing. Applied Sciences, 12(24), 12884. https://doi.org/10.3390/app122412884

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