Network Connected Device Traffic Estimation via Domain Name Queries
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Solution Overview
Problem
Network operators face challenges in providing optimal network management and resource allocation due to varying user requirements for different network application services, as existing methods lack efficient means to estimate network traffic and adjust equipment deployment and resource allocation accordingly.
Innovation Solution
A network connected device and traffic estimation method that captures and analyzes domain name queries to determine network traffic, utilizing machine learning algorithms to estimate service usage behavior and adjust equipment deployment and resource allocation based on the analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If network operators increase hardware equipment and allocate network resources through traditional network management, then network capacity and service coverage are improved, but the ability to precisely estimate network traffic and adapt to varying user requirements deteriorates
Solution Approach 1:
The patent replaces traditional mechanical network management approaches with a machine learning-based system. A processor captures network packets, extracts domain name query information, and uses machine learning algorithms to automatically estimate network traffic and predict user service behavior. This substitution enables precise traffic estimation without requiring complex manual equipment deployment adjustments, resolving the contradiction between estimation accuracy and deployment complexity.
2Measurement precision
If traditional network management methods are used without domain name query analysis, then equipment deployment and resource allocation follow standard procedures, but the precision of network traffic estimation and user behavior prediction deteriorates
Solution Approach 1:
The patent implements a self-service system where the network connected device automatically captures its own network packets, extracts domain name query information, and performs self-analysis using machine learning algorithms. The processor automatically estimates network traffic and predicts user service behavior without external intervention, achieving both high measurement precision and extensive automation simultaneously.
Solution Approach 2:
The system establishes a feedback loop where domain name query information from network packets is continuously captured and analyzed. The machine learning model uses this feedback to refine traffic estimation and behavior prediction accuracy over time, enabling the system to adapt to changing user requirements while maintaining high measurement precision and automation.
3Productivity
If network operators manually adjust equipment deployment and resource allocation, then flexibility in responding to user needs is improved, but the speed and efficiency of traffic estimation and resource optimization deteriorates
Solution Approach 1:
The patent implements preliminary action by using machine learning algorithms to predict future network traffic patterns and user service behavior based on historical domain name query data. The system proactively estimates traffic requirements before peak demand occurs, enabling network operators to pre-configure resource allocation and equipment deployment strategies, thereby eliminating time delays associated with reactive manual adjustments.
Solution Approach 2:
The system dynamically changes operational parameters by continuously analyzing domain name query frequencies and patterns. The machine learning model adjusts traffic estimation parameters and resource allocation parameters in real-time based on observed usage patterns, enabling rapid adaptation to changing network conditions without manual intervention and significantly improving productivity while reducing time loss.
Data Source
AI summary
Embodiments of the disclosure provide a network connected device and a traffic estimation method of the network connected device. In the method, a plurality of network packets are captured, a quantity of query times for at least one domain name in the network packets is counted, and network traffic of each network layer or each service type is determined according to the quantity of query times. In addition, according to the embodiments of the disclosure, a corresponding type feature is generated for a user based on a domain name query record. In this way, the Internet experience of the user may be improved based on the estimated result.