Customized Network Detection for Backend Applications
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Solution Overview
Problem
Traditional network detection solutions fail to provide adequate detection and analysis tools for online content and service providers, particularly in tailoring content for specific clients or network carriers, due to limited detection signals and inflexibility in meeting diverse backend requirements.
Innovation Solution
A method and system for customizing network detection results by identifying client-device connections, obtaining criteria for network-carrier analysis, performing customized analyses, and providing tailored reports to backend applications, which include identifying connection information, determining carrier types, and formatting data for specific backend needs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional network detection solutions are used, then the system structure remains simple, but the detection precision and ability to meet diverse backend requirements deteriorates
Solution Approach 1:
The network detection system is segmented into multiple independent modules: a network detector that collects raw network information, a report generator that processes this information, and multiple specialized backend applications (advertising, analytics, content delivery) that consume customized reports. This segmentation allows each module to be optimized independently, improving detection precision without proportionally increasing overall system complexity.
Solution Approach 2:
The system implements dynamic report generation where the report structure, content, and format are adjusted based on the specific needs of each backend application. The report generator dynamically selects which network detection signals to include and how to format them, allowing the system to adapt to diverse requirements without requiring a completely separate detection system for each application.
2Adaptability or versatility
If traditional network detection solutions are used, then the device complexity is low, but the adaptability to different backend applications deteriorates
Solution Approach 1:
The network detector is designed as a universal component that collects comprehensive network information applicable to multiple different backend applications. The same detection infrastructure serves advertising, analytics, content delivery, and other applications, allowing one system to perform multiple functions and improving adaptability without linearly increasing complexity.
Solution Approach 2:
The system changes parameters of the output reports based on the target application. Different backend applications receive reports with different formats, levels of detail, and selected network signals. This parameter customization allows the system to adapt to various application needs while using a single detection infrastructure.
3Adaptability or versatility
If comprehensive network information is collected for all backend applications, then the adaptability improves, but the loss of information (irrelevant data) increases
Solution Approach 1:
The report generator extracts only the relevant network information needed by each specific backend application from the comprehensive set of collected network signals. For example, advertising applications may only need device type and network carrier information, while analytics applications may need more detailed network performance metrics. This extraction process eliminates irrelevant data before it is processed or stored, reducing information loss.
4Productivity
If traditional network detection is used, then the processing time is short, but the productivity of backend applications deteriorates
Solution Approach 1:
The network detector performs preliminary collection and organization of network information in a standardized format before the report generation step. This preliminary action ensures that when backend applications request reports, the necessary data is already prepared and structured, reducing the processing time required to generate application-specific reports and improving overall productivity.
Data Source
AI summary
A computer-implemented method for customizing network detection results may include identifying a connection between a client device and a frontend server of a web-based computing system. The method may also include obtaining at least one criterion for customizing a network-carrier analysis of the connection for use by a backend application of the web-based computing system. In addition, the method may include performing, based on the criterion, the customized network-carrier analysis of the connection to create a customized report of network-carrier information about the connection. Furthermore, the method may include providing the customized report of network-carrier information to the backend application. Finally, the method may include performing, based on the customized report, at least one task associated with improving a function of the web-based computing system. Various other methods, systems, and computer-readable media are also disclosed.