Network Traffic Classification for QoS Optimization
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Solution Overview
Problem
In enterprise network environments, classifying and prioritizing network traffic for quality of service (QoS) and acceleration techniques is challenging due to diverse communication protocols and varying performance requirements, especially when communications are encrypted or compressed.
Innovation Solution
The system identifies new applications by parsing remote display protocol traffic and adds them to a list for classification, providing QoS and acceleration engines with specific information, enabling enhanced network performance through multi-level classification of network packets.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional classification methods are used, then classification of known applications is achieved, but new applications cannot be identified and classified
Solution Approach 1:
The system performs preliminary parsing of remote display protocol traffic to extract application information before classification is needed. By proactively discovering and storing new application characteristics in advance, the system prepares classification data that will be available when traffic classification occurs, enabling both known and new applications to be properly classified
Solution Approach 2:
The system enables self-service by automatically parsing protocol traffic, extracting application information, and adding new applications to the classification list without manual intervention. The classification engine autonomously discovers new applications through protocol analysis and incorporates them into the classification framework, eliminating the need for manual configuration of new applications
2Adaptability or versatility
If remote display protocol traffic is parsed for new application discovery, then new applications are identified and added to classification list, but system complexity increases
Solution Approach 1:
The system segments the classification functionality into distinct modules: a protocol parsing component that extracts application information from traffic, a classification engine that categorizes traffic based on parsed data, and a database that stores application characteristics. This segmentation allows each component to specialize in specific tasks, reducing overall system complexity while enabling new application discovery
Solution Approach 2:
The patent introduces an intermediary classification engine that sits between the protocol parsing function and the QoS/auction engines. This intermediary processes parsed protocol data, extracts relevant application information, and presents classified results to downstream systems. The intermediary simplifies the architecture by centralizing the classification logic and preventing direct coupling between parsing and application layers
3Productivity
If QoS and acceleration engines receive detailed application information, then network performance is optimized, but information processing overhead increases
Solution Approach 1:
The system extracts only the essential application identification information from parsed protocol traffic and passes this condensed data to QoS and acceleration engines. By extracting only the necessary classification fields rather than transmitting complete protocol details, the system enables performance optimization while minimizing information processing overhead and energy consumption in downstream engines
Data Source
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AI summary
The present invention is directed towards systems and methods for providing discovery of applications for classification of a network packet for performing QoS and acceleration techniques. Remote display protocol traffic associated with a new application not previously included in a list of predetermined applications may be parsed for application information, and the new application may be added to the application list. The remote display protocol traffic may then be classified according to the new application, and network performance may be enhanced and optimized by providing QoS and acceleration engines with packet- or data-specific information corresponding to the newly identified application.