Deployment method of mobile Internet application module

Abstract

The invention discloses a deployment method of a mobile internet application module. The method comprises the steps: firstly, accessing a terminal into a server, acquiring and transmitting the state information of the terminal to the server, calculating an optimal deployment scheme applied on the terminal by applying a bayesian network, and retransmitting the optimal deployment scheme to the terminal through the server, thereby improving the service quality and operation efficiency of the application; secondly, abstracting the application into a plurality of service models, thereby simplifying a topological structure of the application, reducing the complexity of the application, and solving the problem that the calculation execution efficiency of the deployment scheme is low when a past application model is used for complicate application; in the process of operating and applying the terminal, acquiring the basic information of the application module and the state information related in a service model where the terminal is in the operation application process of the terminal, and timely transmitting to the server, and updating an applied bayesian network forecasting model by using these information, therefore a more accurate deployment project can be obtained when a new terminal is accessed.

Description

Technical field [0001] The invention belongs to the field of Internet communication technology, and more specifically, relates to a method for deploying mobile Internet application modules. Background technique [0002] The application of mobile Internet has triggered a profound change in the information industry, and the application has the characteristics of wide distribution and strong mobility. The complete business process of a mobile Internet application generally involves the interaction between the terminal and the server. For example, the smart voice assistant Siri of Apple mobile phones. The mobile terminal collects and recognizes the user’s voice, and then transmits the recognized information to the server. After recognizing this type of information, the user's intention is obtained, and then a knowledge search is performed based on this intention, and the search result is transmitted back to the mobile terminal to show the customer. In this business process, the mobi...

AI Technical Summary

Problems solved by technology

Application deployment algorithms are mainly divided into static algorithms and dynamic algorithms. Static algorithms have high accuracy, but require a large amount of calculation. Generally, the prediction model is calculated in advance through classification or clustering algorithms, which means that a large amount of user data needs to be collected. To complete machine learning, so that when a new user accesses the application, the server can quickly give an appropriate deployment plan; while the dynamic algorithm does not require pre-learning, and performs real-time calculations based on the state of the terminal when it first accesses the application, with high performance and accuracy. Sex is not high

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