Abstract
A new IoT (Internet of Things) analysis platform is designed based on edge computing and cloud collaboration from the perspective of organizational behavior, to fundamentally understand the relationship between enterprise career maturity and career planning, and meet the actual needs of enterprises. The performance of the proposed model is further determined according to the characteristic of the edge near data sources, with the help of factor analysis, and through the study and analysis of relevant enterprise data. The model is finally used to analyze the relationship between enterprise career maturity and career planning through simulation experiments. The research results prove that career maturity positively affects career planning, and vocational delay of gratification plays a mediating role in career maturity and career planning. Besides, the content of career choice in career maturity is influenced by mental acuity, result acuity and loyalty. The experimental results indicate that when the load at both ends of the edge and cloud exceeds 80%, the edge delay of the IoT analysis platform based on edge computing and cloud collaboration is 10s faster than that of other models. Meanwhile, the system slowdown is reduced by 36% while the stability is increased when the IoT analysis platform analyzes data. The results of the edge-cloud collaboration scheduling scheme are similar to all scheduling to the edge end, which saves 19% of the time compared with cloud computing to the cloud end. In Optical Character Recognition and Aeneas, compared with the single edge-cloud coordination mode, the model with the Nesterov Accelerated Gradient algorithm achieves the optimal performance. Specifically, the communication delay is reduced by about 25% on average, and the communication time decreased by 61% compared with cloud computing to the edge end. This work has significant reference value for analyzing the relationship between enterprise psychology, behavior, and career planning.
Highlights
With the rapid development of the Internet, the hardware performance of the computer is constantly improving
Based on the theory of organizational behavior, mobile edge computing is combined with cloud collaboration algorithm to build a data analysis platform based on edge-cloud collaboration, which effectively avoids the subjective evaluation of enterprise personnel for employees
The data analysis platform analyzes the relationship between employee career maturity and career planning through related enterprise data
Summary
With the rapid development of the Internet, the hardware performance of the computer is constantly improving. Cloud computing is a supercomputing mode that integrates large-scale and scalable computing, storage, data, applications and other distributed computing resources for collaborative work in the form of virtualization technology as the basis and the network as the carrier to provide infrastructure, platform, software and other services. Edge cloud computing reduces the response delay, cloud pressure, and bandwidth cost through transferring the network forwarding, storage, calculation, intelligent data analysis, and operation tasks to the edge, and provides cloud services such as whole network scheduling and power distribution. The innovation of this work lies in the use of organizational behavior theory and the combination of edge computing with cloud collaboration to build an IoT analysis platform This platform is applied to analyze the talent data of relevant enterprises to study the relationship between employee career maturity and career planning. The research result has crucial reference significance for understanding the mental health of employees and meeting the needs of enterprises
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