Event Data Structure for Real-Time Network Diagnosis
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Solution Overview
Problem
Wireless service providers face challenges in diagnosing and resolving customer service issues, such as dropped calls, in real-time due to various conditions involving devices, network conditions, and environmental factors, which existing technologies struggle to address effectively.
Innovation Solution
A method and system that detect events related to a target user's equipment within specific time, location, and business constraints, generating event data structures to identify causal events and predict future issues, allowing for adjustments to prevent recurring problems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional network monitoring methods are used, then system complexity is reduced, but real-time diagnosis capability and measurement precision deteriorate
Solution Approach 1:
The patent segments network monitoring into multiple event types (call events, device events, network events, environmental events) and organizes them into structured event data structures with specific dimensions (time, location, business constraints). This segmentation enables precise real-time diagnosis by categorizing and analyzing specific event types without requiring a monolithic complex system, thus improving measurement precision while managing system complexity through modular organization.
Solution Approach 2:
The patent introduces multiple dimensions for event analysis including time constraints, location constraints, and business constraints, transforming traditional single-dimension monitoring into multi-dimensional event data structures. This dimensional expansion enables comprehensive real-time diagnosis by analyzing events from multiple perspectives simultaneously, improving diagnostic precision without proportionally increasing system complexity through efficient dimensional organization.
2Measurement precision
If comprehensive event data collection is implemented, then diagnostic accuracy improves, but information processing time and loss of time increase
Solution Approach 1:
The patent applies preliminary action by pre-defining event data structures with specific dimensions (time, location, business constraints) and pre-categorizing event types before actual diagnosis occurs. Event data is collected and organized into structured formats in advance, so when diagnosis is needed, the pre-organized data can be quickly analyzed without requiring extensive real-time processing, thus improving diagnostic accuracy while minimizing information processing time.
Solution Approach 2:
The patent replaces traditional mechanical sequential processing with a structured data organization system where events are pre-categorized and dimensioned. Instead of processing comprehensive data sequentially during diagnosis, the system uses pre-organized event data structures with defined dimensions that enable faster retrieval and analysis, substituting mechanical processing with an optimized data structure approach that reduces processing time while maintaining diagnostic accuracy.
Data Source
AI summary
Aspects of the subject disclosure may include, for example, a method that includes detecting events relating to user equipment on a communication network, collecting first event data including event times and locations, and collecting second event data regarding second event dimensions determined at least in part by the event type. The method also includes generating, for each of the event types, an event data structure associated with the user, based on the first event data and second event data. The event data structures are concatenated to generate an event history flow associated with the user; the event history flow is analyzed to identify causal events for a detected event. The method also includes generating a model for performance of the user equipment based on the causal events to predict a future event, and identifying potential adjustments to the communication network to prevent that event. Other embodiments are disclosed.