WLAN Management Server Diagnostic Analysis for Connectivity Troubleshooting
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Solution Overview
Problem
Current wireless network troubleshooting methods lack intelligence to identify connectivity issues in WLANs, providing limited information to network administrators, which hampers efficient problem-solving and requires manual effort from administrators.
Innovation Solution
Integration of a WLAN management server with diagnostic functions that perform live or scheduled troubleshooting by analyzing log data from various network nodes, correlating connection states, and providing reports with possible causes and corrective actions to administrators.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If network administrators manually troubleshoot connectivity problems using available information, then they can identify and resolve issues, but the process requires significant manual effort and time
Solution Approach 1:
The system enables self-service troubleshooting by automatically collecting diagnostic data from multiple sources, analyzing connectivity problems, and generating troubleshooting reports without requiring manual administrator intervention. The intelligent analysis engine autonomously processes log data, client information, and network state data to identify root causes and suggest corrective actions.
Solution Approach 2:
The system performs preliminary troubleshooting actions by proactively collecting and analyzing diagnostic data before administrators need to intervene. The intelligent analysis engine continuously monitors network state and prepares troubleshooting reports in advance, so when connectivity problems occur, administrators receive pre-analyzed information with suggested solutions ready for immediate implementation.
2Measurement precision
If the system collects and analyzes comprehensive log data from multiple network nodes, then diagnostic accuracy improves, but system complexity increases
Solution Approach 1:
The intelligent analysis engine serves as an intermediary that simplifies the complex task of analyzing comprehensive log data from multiple network nodes. It automatically collects, correlates, and analyzes data from wireless clients, access points, controllers, and other network elements, transforming raw complex data into actionable diagnostic information with identified root causes and suggested corrective actions.
3Productivity
If automated diagnostic functions are implemented, then troubleshooting efficiency improves, but the initial system setup and integration complexity increases
Solution Approach 1:
The intelligent analysis engine is designed as a universal platform that can analyze connectivity problems across diverse wireless network configurations and equipment vendors. It handles multiple data sources including wireless clients, access points, controllers, and various network elements through a unified diagnostic framework, reducing the need for vendor-specific implementations and simplifying system integration.
Data Source
AI summary
A troubleshooting system. In particular implementations, a method includes collecting, from a first wireless network element, PEM state associated with a wireless client having a connection problem, and collecting log data associated with the wireless client from the first wireless network elements and one or more other wireless network elements. The method further includes correlating the PEM state and log data based on a network security protocol employed by the wireless client, where the network security protocol corresponds to an expected sequence of events. The correlating includes correlating events and messages collected based on the expected sequence of events, and comparing the correlated sequence of events to a data store of diagnostic information to identify one or more possible causes of the connection problem.