Adaptive Message Queue Timeouts for Storage Systems
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Solution Overview
Problem
Current message queue systems in storage systems often require frequent reconnections due to finite connection resources, leading to substantial extraneous processing and delays in notification retrieval, as applications poll continuously with short timeout values, resulting in inefficient resource utilization and real-time processing.
Innovation Solution
Implementing adaptive message queue timeouts based on storage system access characteristics, such as access rates and concurrent connections, to dynamically adjust timeout values, reducing unnecessary reconnections and enhancing real-time processing efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If short timeout values are used for message queue connections, then real-time notification retrieval is improved, but frequent reconnections occur leading to substantial extraneous processing
Solution Approach 1:
The patent applies dynamics by making the timeout value adjustable rather than fixed. The message queue timeout is dynamically modified based on storage system access characteristics, allowing the system to adapt between short timeouts (for real-time responsiveness) and long timeouts (for reducing reconnection frequency) according to actual workload conditions
Solution Approach 2:
The patent changes the timeout parameter based on storage system access patterns. By monitoring characteristics such as access frequency and notification volume, the system adjusts the timeout value to optimize the balance between real-time retrieval and minimizing extraneous reconnection processing
2Productivity
If continuous polling with short timeout values is implemented, then real-time processing is enhanced, but resource utilization becomes inefficient
Solution Approach 1:
The system dynamically adjusts the polling timeout based on storage system activity characteristics. When access patterns indicate low activity, longer timeouts reduce unnecessary polling frequency and resource consumption. When high activity is detected, shorter timeouts maintain real-time responsiveness, thus optimizing resource utilization across varying workload conditions
Solution Approach 2:
The patent implements feedback by monitoring storage system access characteristics and using this information to adjust timeout values. This closed-loop approach allows the system to learn from actual workload patterns and optimize resource usage by adapting polling frequency to match actual notification generation rates
Data Source
AI summary
A first set of storage accesses of a storage system are identified. The first set of storage accesses are associated with a first user. A first plurality of storage access notifications is sent to a first message queue associated with the first user based on the first set of storage accesses. A first message queue timeout value of the first message queue is set based on at least one characteristic associated with the first set of storage accesses.