Network Traffic Analysis Using Segmentation and Modeling
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Solution Overview
Problem
Conventional network monitoring systems provide insufficient detail and resolution, leading to suboptimal network configuration and inability to predict performance changes due to transformations like compression or suppression of network traffic.
Innovation Solution
A method and system that involves sampling network traffic data, creating traffic descriptors, transforming the data, and modeling bandwidth requirements and quality of service settings to optimize network performance, while also projecting the effects of transformations on network traffic.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional monitoring systems are used, then network traffic information is provided, but the detail and resolution are insufficient leading to suboptimal network configuration
Solution Approach 1:
The patent segments network traffic into multiple classes based on application type, protocol, and other characteristics. This segmentation enables detailed analysis of specific traffic patterns while maintaining overall network visibility, resolving the contradiction between providing sufficient detail and maintaining system manageability.
Solution Approach 2:
The patent adds temporal and spectral dimensions to network traffic analysis by implementing time-varying spectral analysis. This multi-dimensional approach provides detailed traffic information across different time scales and frequency components, enabling precise measurement without overwhelming complexity.
2Adaptability or versatility
If conventional monitoring systems are used, then network traffic is monitored, but the ability to predict performance changes with transformations like compression is lost
Solution Approach 1:
The patent performs preliminary characterization of network traffic by building statistical models and analyzing traffic patterns before actual network transformations are applied. This advance analysis enables prediction of performance changes due to compression, encryption, or other transformations without requiring the actual transformations to occur first.
Solution Approach 2:
The patent creates virtual copies of network traffic through detailed modeling and simulation. These traffic models replicate actual network behavior and can be used to predict performance under various transformation scenarios, providing adaptability without requiring multiple physical monitoring systems.
3Productivity
If detailed network traffic analysis is implemented, then network performance can be optimized, but the system complexity increases
Solution Approach 1:
The patent extracts only the essential and relevant features from network traffic data for analysis, rather than processing all raw data. By identifying and extracting key performance indicators and traffic characteristics, the system achieves effective optimization with reduced computational complexity.
Solution Approach 2:
The patent implements analysis at multiple levels of detail, applying comprehensive analysis only where needed and simplified analysis elsewhere. This partial action approach focuses computational resources on critical network segments and traffic types, achieving effective optimization without uniformly high complexity across the entire system.
Data Source
AI summary
A method and system for optimizing network traffic settings and for providing information on projected optimization of transformed traffic for a network includes: providing a traffic descriptor for sampled traffic data of the network; transforming the traffic data and extracting information on the transformed traffic data; and providing the traffic descriptor and the information on the transformed traffic data for analysis. The information can be a transformation traffic descriptor or a delta between untransformed and transformed network traffic. The traffic data and the transformed traffic data can then be modeled based the traffic descriptor and the information, respectively. Bandwidth requirements and quality of service settings for optimizing network performance for a service level can be provided based upon the traffic data model. Information on projected optimization of transformed network traffic can also be provided for the service level based upon the transformed traffic data model.