Mapping Structure Workload Estimation for Page Removal
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Solution Overview
Problem
The unpredictable workload associated with removing pages from a mapping structure in data storage systems leads to inefficient resource allocation and performance issues, as underestimating or overestimating the processing required can result in throttling I/O requests, impacting customer applications.
Innovation Solution
A technique that identifies the levels of pages to be removed and estimates the workload based on these levels, allowing for intelligent resource allocation by initiating processing when the estimated workload exceeds a threshold.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the storage system processes the collection bin periodically without accurate workload prediction, then real-time I/O activities can continue uninterrupted, but the processing workload becomes unpredictable causing potential throttling or resource waste
Solution Approach 1:
The system performs preliminary estimation of the workload required to process pages in the collection bin by analyzing the mapping structure levels before actual processing begins. This preliminary action allows the system to predict resource requirements and plan processing timing accordingly, avoiding both premature throttling and resource waste.
Solution Approach 2:
The system continuously monitors the collection bin and estimates workload based on the current state of the mapping structure. This feedback mechanism allows dynamic adjustment of processing timing and resource allocation, improving both productivity and workload predictability by adapting to changing system conditions.
2Loss of energy
If the storage system underestimates the workload for processing the collection bin, then resource allocation is reduced, but I/O requests must be throttled to complete processing, impacting customer applications
Solution Approach 1:
The system replaces simple count-based thresholds with a more sophisticated workload estimation mechanism that analyzes mapping structure levels. This substitution allows for more accurate prediction of processing requirements, enabling the system to allocate resources appropriately without needing to throttle I/O requests.
3Reliability
If the storage system overestimates the workload for processing the collection bin, then resources are allocated for processing, but resources are wasted when they could be used for more critical tasks
Solution Approach 1:
The system changes the parameter for workload assessment from a fixed threshold approach to a dynamic estimation based on mapping structure levels. By analyzing which levels contain pages and calculating workload accordingly, the system achieves more accurate resource prediction, allocating resources only when necessary while avoiding waste during low-workload periods.
Data Source
AI summary
A technique for managing a mapping structure in a data storage system includes identifying levels in the mapping structure of pages to be removed and estimating the workload required for removing the pages based at least in part on the identified levels. The technique further includes initiating processing of the pages based at least in part on the estimated workload.