The Research And Implementation Of Mobile Network Data Intelligent Management System

With the progress of 4G mobile communication network technology,the construction center of communication networks has changed.Mobile users have put forward higher requirements on not only guarantee basic network communication service,but also must ensure the speed and quality of network operations.The direction of mobile network optimization should also be based on user-critical data as the top priority.At the same time,the daily working methods of the mobile network optimization department have also changed.It is difficult to analyze massive amounts of user data by traditional report analysis methods.You should need to use intelligent systems to manage and analyze data.After collecting mobile network user data,network optimization staff analyze these data and infer which business indicators will affect the quality of the network.By do it ensuring that the mobile communications network is in the best operating condition.This paper proposes and designs a mobile network data intelligent management system.The system needs to get data from the database frequently.User data brings great challenges to database design.This paper designs a table storage structure that best meets the characteristics of user data by using storage segmentation and data wide table construction.In term of optimizing database execution speed,we design data indexing and storage procedures.The cache technology is applied to the database and web pages to save duplicate data to the memory,which greatly speeds up data acquisition and improves system performance.This system presents two types of map presentation and chart presentation.In order to be able to present the indicator data to the map,this paper implements the application of geographic rasterization technology to Zhuhai City's regional division.The cell coverage model algorithm and its update strategy are studied and used to implement the cell and grid coverage relationship.Finally,network optimization staff view the network quality through to the data visualization.