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Sensors
Volume 25
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10.3390/s25010259
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Article

The Construction of a Stream Service Application with DeepStream and Simple Realtime Server Using Containerization for Edge Computing

by
Wen-Chung Shih
1,
Zheng-Yao Wang
2,
Endah Kristiani
2,3,
Yi-Jun Hsieh
2,
Yuan-Hsin Sung
2,
Chia-Hsin Li
4 and
Chao-Tung Yang
2,5,*
1
Department of M-Commerce and Multimedia Applications, Asia University, Taichung City 413305, Taiwan
2
Department of Computer Science, Tunghai University, Taichung City 407224, Taiwan
3
Department of Informatics, Krida Wacana Christian University, Jakarta 11470, Indonesia
4
iAMBITION TECHNOLOGY Co., Ltd., 3F., No. 159-1, Sec. 1, Zhongxing Rd., Dali District, Taichung City 412031, Taiwan
5
Research Center for Smart Sustainable Circular Economy, Tunghai University, No. 1727, Sec. 4, Taiwan Boulevard, Taichung City 407224, Taiwan
*
Author to whom correspondence should be addressed.
Sensors 2025, 25(1), 259; https://doi.org/10.3390/s25010259
Submission received: 19 December 2024 / Revised: 1 January 2025 / Accepted: 2 January 2025 / Published: 5 January 2025
(This article belongs to the Section Communications)
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Abstract

This paper addresses the increasing demand for efficient and scalable streaming service applications within the context of edge computing, utilizing NVIDIA Jetson Xavier NX hardware and Docker. The study evaluates the performance of DeepStream and Simple Realtime Server, demonstrating that containerized applications can achieve performance levels comparable to traditional physical machines. The results indicate that WebRTC provides superior low-latency capabilities, achieving delays of around 5 s, while HLS typically experiences delays exceeding 10 s. Performance tests reveal that CPU usage for WebRTC can exceed 40%, which is higher than that of HLS and RTMP, while memory usage remains relatively stable across different streaming protocols. Additionally, load testing shows that the system can support multiple simultaneous connections, but performance degrades significantly with more than three devices, highlighting the limitations of the current hardware setup. Overall, the findings contribute valuable insights into building efficient edge computing architectures that support real-time video processing and streaming.
Keywords: Docker; edge computing; simple realtime server; deepstream; Jetson Xavier NX Docker; edge computing; simple realtime server; deepstream; Jetson Xavier NX

Share and Cite

MDPI and ACS Style

Shih, W.-C.; Wang, Z.-Y.; Kristiani, E.; Hsieh, Y.-J.; Sung, Y.-H.; Li, C.-H.; Yang, C.-T. The Construction of a Stream Service Application with DeepStream and Simple Realtime Server Using Containerization for Edge Computing. Sensors 2025, 25, 259. https://doi.org/10.3390/s25010259

AMA Style

Shih W-C, Wang Z-Y, Kristiani E, Hsieh Y-J, Sung Y-H, Li C-H, Yang C-T. The Construction of a Stream Service Application with DeepStream and Simple Realtime Server Using Containerization for Edge Computing. Sensors. 2025; 25(1):259. https://doi.org/10.3390/s25010259

Chicago/Turabian Style

Shih, Wen-Chung, Zheng-Yao Wang, Endah Kristiani, Yi-Jun Hsieh, Yuan-Hsin Sung, Chia-Hsin Li, and Chao-Tung Yang. 2025. "The Construction of a Stream Service Application with DeepStream and Simple Realtime Server Using Containerization for Edge Computing" Sensors 25, no. 1: 259. https://doi.org/10.3390/s25010259

APA Style

Shih, W.-C., Wang, Z.-Y., Kristiani, E., Hsieh, Y.-J., Sung, Y.-H., Li, C.-H., & Yang, C.-T. (2025). The Construction of a Stream Service Application with DeepStream and Simple Realtime Server Using Containerization for Edge Computing. Sensors, 25(1), 259. https://doi.org/10.3390/s25010259

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