Application of Basketball Training System Based on Dynamic Intelligent Fog Computing Network

Abstract

Although the development of the mobile Internet and the Internet of Things has greatly promoted the progress and development of society, it has also created many problems for people on the road of scientific and technological exploration. In order to meet the problems and requirements of high bandwidth, high load, and low latency in the current network development, the emergence of the concept of mobile edge computing has attracted extensive attention from the academic community. This article focuses on the representative mode of mobile edge computing-fog computing (in this model, data, (data)processing, and applications are concentrated in devices at the edge of the network, instead of being stored almost entirely in the cloud). By applying it to the development and operation of basketball training system, it explores the performance of dynamic intelligent fog computing in intelligent end user services. This paper proposes a fog resource scheduling scheme based on linear weighted genetic algorithm, which converts the problem of multiobjective optimization into a single-objective optimization problem. When applying the genetic algorithm based on weighted sum, preference is given to delay, communication load, and service cost. Value is integrated into an objective function to perform genetic operations to get a better solution. From the experimental data, the system can support 20 DCTU terminals with a pressure request of 10 messages per second per terminal under the pressure environment created by the pressure test input data. The barrier-free transmission distance is 200 m, and the barrier transmission distance is 50 m. It has strong fault tolerance.