Dynamic Queue Depth Management for Message Loss Prevention
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Solution Overview
Problem
Existing queue management systems face disruptions and inefficiencies when queue depths exceed preset thresholds, leading to potential message loss and increased computer memory allocation, as they lack automated mechanisms to dynamically adjust queue settings in response to alarm conditions.
Innovation Solution
The system automatically increases the queue depth when it exceeds a high-depth-alarm setting, allowing additional messages to be received while the cause is addressed, and subsequently resets the depth when the condition is resolved, optimizing memory allocation and preventing disruptions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the queue depth is increased to prevent message loss during incidents, then message processing continuity is improved, but computer memory allocation increases
Solution Approach 1:
The queue maximum depth is made dynamic rather than static. The system automatically adjusts the queue depth based on incident status: increasing depth when incidents are detected to prevent message loss, and decreasing depth when incidents are resolved to optimize memory usage. This dynamic adjustment resolves the contradiction by allowing the queue to adapt its resource consumption to actual operational needs.
Solution Approach 2:
The system changes the parameter of queue maximum depth in response to incident conditions. When a high-depth alarm is triggered indicating an incident, the maximum depth parameter is increased to accommodate additional messages. When the incident is resolved, the parameter is decreased back to original levels, thus optimizing memory allocation while maintaining reliability during critical periods.
2Productivity
If automated mechanisms are implemented to dynamically adjust queue settings, then operational efficiency is improved, but device complexity increases
Solution Approach 1:
The system implements feedback mechanisms through high-depth alarms that monitor queue conditions and trigger automated responses. When the queue depth exceeds thresholds indicating an incident, the system receives feedback and automatically adjusts the maximum depth setting. This feedback loop enables operational efficiency through automation while keeping the complexity manageable by focusing on specific critical thresholds rather than continuous complex control.
Solution Approach 2:
The queue management system performs self-service by automatically detecting incidents through alarm conditions and adjusting its own maximum depth parameter without requiring manual intervention. The system monitors its own state, identifies when incidents occur, and autonomously modifies its configuration to prevent message loss, thereby improving operational efficiency while minimizing the need for complex external control systems.
Data Source
AI summary
A method and system for automatically managing alarms in an environment where a period of time could pass before the cause of the alarm is addressed is explained herein. The method includes automatically increasing the maximum depth of a queue (i.e. the maximum capacity of a queue to store data) in response to an indication that the current depth of the queue exceeds a high-level alarm setting. Upon determining that the depth of the queue has fallen below the original high-level alarm setting, the maximum depth of the queue is automatically returned to the original maximum setting. In addition, a low-level alarm may be disabled in conjunction with increasing the maximum depth and reactivated upon returning the maximum queue depth to the original setting.