Wireless Network Alarm Monitoring with Event Quality Metrics
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Solution Overview
Problem
Existing wireless telecommunication networks face challenges in efficiently monitoring and managing the vast volume of operational messages from multiple components, leading to issues such as duplicate alarms, lack of clear restoration indicators, and inefficient issue resolution.
Innovation Solution
A system and method for monitoring and evaluating the operation of wireless telecommunication networks that filters, correlates, and prioritizes alarms based on importance, using connectivity and service topology to reduce duplicates and automate alarm generation, while generating metrics for effective issue management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a monitoring system continuously monitors voluminous messages from multiple components, then the operational status can be determined, but the system complexity and message volume increase
Solution Approach 1:
The monitoring system is segmented into specialized modules: a message source component that generates messages, a message router that distributes messages to subscriber components, and multiple subscriber components that monitor specific aspects. This segmentation allows the system to handle voluminous messages through distributed specialization rather than centralized processing, reducing overall system complexity while maintaining comprehensive monitoring capability.
Solution Approach 2:
A message router acts as an intermediary between message sources and subscriber components. The router receives messages from various sources and intelligently distributes them to appropriate subscribers based on message type and subscriber interests. This intermediary layer simplifies the architecture by centralizing the routing logic and preventing direct complex interactions between all message sources and all subscribers.
2Reliability
If all operational messages are monitored and alarmed, then complete coverage is achieved, but duplicate alarms and noise increase
Solution Approach 1:
Each subscriber component is configured with specific interests and filters tailored to its local monitoring needs. Subscriber components selectively process only the messages relevant to their specific function or component type, rather than processing all messages uniformly. This local quality approach ensures complete coverage of different monitoring aspects while reducing duplicate alarms through selective filtering at each monitoring point.
Solution Approach 2:
The system implements partial monitoring through selective subscription where each subscriber component monitors only a subset of messages relevant to its function. This partial action approach avoids the excessive processing of all messages by every component, reducing noise and duplicate alarms while maintaining adequate monitoring coverage for critical operations.
3Ease of operation
If manual analysis of alarms is performed, then flexibility is maintained, but issue resolution time increases
Solution Approach 1:
The monitoring system performs self-service through automated message routing and filtering. Subscriber components automatically receive and process relevant messages without requiring manual intervention for message distribution. The system self-configures which components receive which messages based on predefined subscription criteria, reducing manual analysis time while maintaining operational flexibility through configurable subscription rules.
Solution Approach 2:
Message routing and filtering rules are configured in advance before monitoring begins. Subscriber components are pre-subscribed to specific message types and sources based on their monitoring requirements. This preliminary configuration enables automated, immediate response to relevant messages without requiring manual analysis or routing decisions when events occur, significantly reducing issue resolution time while preserving flexibility through the pre-configured rules.
Data Source
AI summary
A system generates metrics associated with a monitoring system of a wireless telecommunication network. The monitoring system analyzes importance of multiple messages generated by multiple components of the network and, based on the analysis, generates multiple alarms. The metrics include an event coherence metric, an event significance metric, an event knowledge metric, and an event quiescence metric. The event coherence metric indicates a number of the multiple alarms including sufficient information to aid in issue resolution. The event significance metric indicates a number of the multiple alarms resulting in an issue ticket creation. The event knowledge metric indicates a number of the multiple alarms including documentation associated with the alarm. The event quiescence metric indicates a number of the multiple alarms that have at most a predetermined number of alarms generated per issue. The system generates a report including the event coherence metric, significance metric, knowledge metric, and quiescence metric.