Construction of an Intelligent APP for Dance Training Mobile Information Management Platform Based on Edge Computing

Author:

Gao Yan12,Xu Dazhi34ORCID

Affiliation:

1. College of Art, Hunan University of Arts and Science, Changde 415000, Hunan, China

2. School of Management, Shinawatra University, Thani, Bangkok 12160, Thailand

3. College of Economics and Management, Hunan University of Arts and Science, Changde 415000, Hunan, China

4. Public Administration, Central South University, Changsha 410083, Hunan, China

Abstract

In recent years, with the rapid development of modern technology and the continuous promotion of information technology, information technology has been widely used in modern performing arts. Information management has become the most practical and effective method and means in performing arts training management, but as the amount of various data grows exponentially, the requirements for computing processing power and speed for massive amounts of data and information are also increasing day by day. This article aims to study the use of edge computing to solve the problems of high latency and high cost when traditional cloud computing centers provide services. In response to these problems, this paper proposes a data acquisition and processing system architecture based on edge computing, which uses edge computing to mine the computing power of edge terminals in the network, performs partial or all calculations at the edge terminals, processes private data, and reduces cloud computing. The center’s computing, transmission bandwidth load, and energy consumption, combined with cloud computing, provide data acquisition, processing, and analysis solutions with low latency and high processing capabilities. This article details how to optimize edge server development to minimize access latency and consider network reliability when requesting access to edge servers. This paper uses the proposed edge server deployment algorithm and system load optimization, which can effectively reduce the network delay and system load of the edge server, and the experimental results show that the system performance is improved by 23.5% after effective optimization.

Funder

Project of Hunan Provincial Social Science Achievement Review Committee

Publisher

Hindawi Limited

Subject

Computer Networks and Communications,Computer Science Applications

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