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

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.