The Human-in-the-Loop Data Sensing Architecture Based on Edge Cloud Computing

J. Sensors Pub Date : 2022-08-21 DOI:10.1155/2022/9542290

Chen Gao

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引用次数: 1

Abstract

The cloud system structure is limited by sensor data processing to handle real-time constancy and mobility. To solve such a problem, this paper proposes a system structure based on edge cloud computing and human perception of data in the ring and explores its application in big data analysis. Specifically, a three-layer data flow computing structure composed of a wireless network, edge cloud system, and central cloud system is constructed. In terms of data flow structure, a mobile service structure supporting real-time operation and mobility is proposed. Based on such a structure, an edge cloud data awareness structure is further proposed. Moreover, a flexible storage structure that can be used to support different types of applications is designed to optimize the sensor system and improve the reliability of data storage. The experimental results show that the system structure based on edge cloud terms reduces the server failure rate and total utilization due to the capacity of VMs. Besides, its performance is much better than the existing structure in terms of maintenance and data processing time. Finally, the result of the edge of the cloud computing solution can save 19% on time than the original scheme.

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基于边缘云计算的人在环数据感知架构

云系统结构受到传感器数据处理的限制，无法处理实时的稳定性和移动性。针对这一问题，本文提出了一种基于边缘云计算和人对环内数据感知的系统结构，并探索其在大数据分析中的应用。具体而言，构建了由无线网络、边缘云系统和中心云系统组成的三层数据流计算结构。在数据流结构方面，提出了一种支持实时操作和移动性的移动业务结构。在此基础上，进一步提出了一种边缘云数据感知结构。此外，还设计了可支持不同类型应用的灵活存储结构，以优化传感器系统，提高数据存储的可靠性。实验结果表明，基于边缘云的系统结构由于虚拟机的容量，降低了服务器故障率和总利用率。此外，在维护和数据处理时间方面，它的性能比现有的结构要好得多。最后，边缘云计算解决方案的结果比原方案节省19%的时间。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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J. Sensors

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