Dynamic Priority Adjustment for Parallel Message Queue Load Balancing
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Solution Overview
Problem
In messaging-middleware environments, primary queue instances experience decreased throughput, leading to inefficient message delivery due to unbalanced load distribution among parallel queue instances, where conditions prevent increasing priority settings for other queue instances, and a high number of application interfaces operate, causing message bottlenecks.
Innovation Solution
A method is implemented to automatically lower the priority setting of the primary queue instance when message throughput falls within a cautionary range, determined by monitoring characteristics such as message entry and exit rates, and the number of application interfaces, ensuring that conditions do not allow priority increases for parallel queue instances, thereby rerouting messages to other queue instances.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the priority setting of the primary queue instance is increased to improve message delivery, then message throughput is improved, but system stability deteriorates due to unbalanced load distribution
Solution Approach 1:
The patent implements dynamic priority adjustment for queue instances based on real-time monitoring of message throughput and application interface counts. The system automatically increases or decreases priority settings of specific queue instances in response to changing system conditions, transforming a static load balancing approach into a dynamic one that adapts to current system state, thereby resolving the contradiction between improving throughput and maintaining stability
Solution Approach 2:
The system continuously monitors message throughput and application interface counts for each queue instance, using this feedback information to automatically adjust priority settings. When a queue instance shows decreased throughput and has sufficient application interfaces, its priority is increased to improve message delivery, while the system monitors the effects and adjusts accordingly, creating a closed-loop control system that balances throughput improvement with system stability
2Productivity
If the number of application interfaces is increased to handle more messages, then message processing capacity is improved, but system complexity increases
Solution Approach 1:
The system automatically monitors and manages application interface counts for each queue instance without requiring manual intervention. When a queue instance's throughput decreases and it has fewer than a threshold number of application interfaces, the system automatically increases the interface count to improve processing capacity, and vice versa. This self-managing approach increases capacity while minimizing the complexity burden on operators
Data Source
AI summary
A method, system, and medium are provided for re-routing messages from a particular parallel queue instance that is experiencing below normal message throughput by lowering the priority setting of the particular queue instance. The messages are re-routed to the other parallel queue instances by a load balancing algorithm that transfers messages to queue instances having a higher priority setting. A series of determinations are made, prior to lowering the priority setting, to confirm that lowering the priority setting for the queue instance is the preferred response to the decreased throughput for the queue instance.