Network Port Characterization Through Traffic Analysis and Machine Learning
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Solution Overview
Problem
Managing device configuration in network switches is challenging due to the reliance on outdated manual documentation, which can lead to errors and requires costly support for issue resolution, and is dependent on the type of network traffic transmitted and received via the device or port.
Innovation Solution
A method and system for characterizing network traffic on multi-port network devices by receiving data that includes rankings and ratios, using machine learning to determine port types, and outputting indicators for optimized configuration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual documentation is used to track network device configuration, then implementation cost is low, but reliability of configuration information deteriorates due to outdated and error-prone documentation
Solution Approach 1:
The system enables automatic self-characterization of network ports by having the network device itself generate and update configuration data based on observed traffic patterns, eliminating the need for external manual documentation while ensuring the information remains current and accurate
Solution Approach 2:
The system implements continuous monitoring of network traffic through the port characterization module, which feeds back configuration recommendations to the network administrator, creating a closed-loop system that automatically updates documentation based on actual traffic observations
2Productivity
If manual configuration management is used, then device complexity is low, but productivity deteriorates due to time-consuming manual updates and costly support requirements
Solution Approach 1:
The system replaces the mechanical process of manual documentation with an automated electronic characterization system that uses machine learning models and traffic analysis to automatically generate and update configuration information, dramatically increasing update speed while reducing human intervention
Solution Approach 2:
The system performs preliminary characterization of port types by analyzing traffic patterns before configuration decisions are needed, allowing the network administrator to receive pre-analyzed recommendations that speed up the configuration process without requiring complex real-time analysis
Data Source
AI summary
An example method includes receiving, from a network device, data indicating characterizations of network traffic on a plurality of ports of the network device; determining, by processing circuitry, for each port of the plurality of ports, an indicator of a port type for the port based on the data indicating the characterizations of network traffic on the plurality of ports, wherein the port type indicates a link type of network traffic exchanged by the port; and outputting, by the processing circuitry, the indicator of the port type to an output device.