Design And Implementation Of Edge Warning System Of Multi-Network Computing Resource Joint

In recent years,the rapid development of mobile wireless network and Internet of Things technology has led to the rapid growth of network connection element and data transmission,and the traditional cloud computing model has gradually failed to meet the daily needs.Therefore,edge computing,a new computing model,has gradually become popular.As a complement to cloud computing,edge computing aims to reduce the strain on the backbone and the cost of data transmission.However,in the actual application environment,the edge services are usually deployed in or near the mobile communication base station,leading to the isolation of computing resources between different operators,which will result in a certain waste of computing resources and the failure of real-time execution of users' computing tasks.How to improve the utilization of computing resources of edge nodes as much as possible under the condition of ensuring user experience has become an urgent problem to be solved.In this paper,by putting forward the fusion of multi-network computing resources and combining with the existing general architecture of edge computing,a scheme of multi-network computing resources integration is designed,and edge nodes in different operator networks are uniformly allocated to perform computing tasks.Internet of Things technology is an important application direction of edge computing.In the construction process of "smart prison",there are outgoing scenarios such as going out for medical treatment and transferring prisoners to other places.In order to better face emergencies when going out,this paper designs and implements an edge warning system,which collects real-time information of prisoners by using some Internet of Things devices and analyzes the information,so as to achieve the role of intelligent risk assessment of prisoners and provide help for law enforcement officers.The edge computing model is introduced into the edge warning system,which greatly reduces the data transmission delay and improves the response rate of the system.At the same time,considering the randomness of the region in the outbound task,the signal quality of the operators' public network in each region varies,and deployed edge nodes also have different computing power.In the long-distance escort,only the computing service of a certain operator is used,which may result in poor data transmission quality or insufficient computing resources due to the existence of blind areas of coverage,thus failing to guarantee the stability of the whole service.Therefore,the system adopts the method of multi-network computing resource integration to design.In addition,artificial intelligence and the Internet of Things technology are gradually mature,and the combination of the two makes it possible for systems to gradually add more service functions in the future.In order to improve the flexibility of function upgrading and deployment in the future,this paper adopts the design idea of micro-service architecture to develop the system.