Network Virtualization for Root Cause Analysis Event Elimination
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Solution Overview
Problem
Existing root cause analysis techniques in network management systems are inefficient, often taking too long to converge or failing to identify root causes due to large event numbers and missing key events, and struggle with configuring time windows to exclude irrelevant events while including relevant ones, especially when network problems propagate at different rates and locations.
Innovation Solution
The approach involves creating a virtual network model that represents nodes and links at various time periods, using topological information to eliminate candidate events that are not on the path associated with the given event, thereby accurately determining the root cause by simulating network paths and leveraging network virtualization to restrict the search space.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If existing root cause analysis techniques use causality graphs constructed from collected events, then root cause analysis can be performed, but the convergence time becomes inordinately long or the analysis fails to converge
Solution Approach 1:
The patent extracts and removes irrelevant events from the analysis by using network topology information to identify and eliminate events that cannot be root causes. This filtering approach reduces the event set to only those that could potentially be root causes, significantly improving convergence speed while maintaining analysis reliability.
Solution Approach 2:
The patent segments the root cause analysis process into multiple filtering stages: first filtering by time window, then filtering by network topology relevance. This segmentation allows the system to progressively reduce the event set through manageable steps, improving overall convergence efficiency.
2Productivity
If existing techniques configure a time window to exclude irrelevant events, then efficiency is improved, but it becomes difficult to properly configure the window to include relevant events while excluding irrelevant ones
Solution Approach 1:
The patent introduces network topology information as an intermediary filtering mechanism between the time window filter and the final root cause identification. This intermediary uses topological relationships to automatically filter events, eliminating the need for complex manual time window configuration while maintaining high efficiency.
3Device complexity
If existing techniques use single hop root cause analysis, then the analysis is simplified, but the system cannot identify root causes residing more than one hop from the symptom
Solution Approach 1:
The patent adds the network topology dimension to the traditional time-based filtering approach. By incorporating topological information about network paths and relationships, the system can identify root causes at any distance from the symptom while maintaining manageable complexity through structured filtering criteria.
Data Source
AI summary
Root cause analysis in a communication network includes eliminating candidate events using a computer-implemented method, comprising creating a virtual network model that describes nodes and links of the network at a plurality of time periods; receiving from the network a first event that indicates a problem in the network; receiving a set of second events comprising candidates for a root cause of the first event; determining a network topological indicator from the first event; determining a network implication of the first event based on the topological indicator; based on the network implication and a time value of the first event, retrieving data from the virtual network model that indicates a path between nodes associated with the first event at a time at which the first event occurred; removing, from the set of second events, all events that are not on the path between devices associated with the first event.