A Low Latency Processing System Architecture Strategy for Edge Service Nodes in Fog Computing

This paper proposes a low latency processing system architecture strategy for edge service nodes in fog computing to address the network latency issue in the cloud based monitoring system in shipyards. By utilizing the characteristics of fog computing that are closer to terminal devices, local image acquisition devices directly send the collected image data to the fog server for processing, overcoming the problems of network latency and excessive network usage under the cloud monitoring system architecture. The main motivation for using fog computing in the proposed method is to minimize the delay and network usage generated by the entire monitoring system during image transmission and processing. To demonstrate the effectiveness of the proposed method in reducing latency and network usage, this paper conducted simulation validation on the fog computing monitoring system architecture in iFogSim and compared the results with cloud based monitoring systems. The experimental results show that the fog based monitoring system proposed in this article significantly reduces the delay and network usage generated during image transmission and processing.

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Publication Details

Published
2024-10-18
DOI
https://doi.org/10.1109/iccsn63464.2024.10793367
Primary Topic
Energy Efficient Wireless Sensor Networks
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article
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article

A Low Latency Processing System Architecture Strategy for Edge Service Nodes in Fog Computing

Zhenyu Yin, Yue Ma, Zhiying Bi, Chengen Ju
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Energy Efficient Wireless Sensor Networks
article

A Low Latency Processing System Architecture Strategy for Edge Service Nodes in Fog Computing

Zhenyu Yin, Yue Ma, Zhiying Bi, Chengen Ju
article en

Abstract

This paper proposes a low latency processing system architecture strategy for edge service nodes in fog computing to address the network latency issue in the cloud based monitoring system in shipyards. By utilizing the characteristics of fog computing that are closer to terminal devices, local image acquisition devices directly send the collected image data to the fog server for processing, overcoming the problems of network latency and excessive network usage under the cloud monitoring system architecture. The main motivation for using fog computing in the proposed method is to minimize the delay and network usage generated by the entire monitoring system during image transmission and processing. To demonstrate the effectiveness of the proposed method in reducing latency and network usage, this paper conducted simulation validation on the fog computing monitoring system architecture in iFogSim and compared the results with cloud based monitoring systems. The experimental results show that the fog based monitoring system proposed in this article significantly reduces the delay and network usage generated during image transmission and processing.

Chinese Academy of Sciences (CN), Shenyang Institute of Computing Technology (China) (CN)
Affordable and clean energy
Openalex Percentile: Top 73%
Energy Efficient Wireless Sensor Networks
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