Storage Cache Page Allocation for Hit Ratio and Delay Control
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Solution Overview
Problem
Existing memory resource allocation methods in storage systems result in reduced hit ratios and increased service processing delays due to uniform eviction of cache objects, particularly those with large page resource requirements, leading to inefficient utilization of memory resources.
Innovation Solution
A resource allocation method and apparatus that adjusts page resource allocation based on a first model indicating the resource needed to meet a specific hit ratio, using weight values, historical information, and statistical data to optimize resource distribution among cache objects, thereby improving memory pool utilization and reducing service processing delays.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If resource allocation is based on historical data and simple algorithms, then implementation is simple, but resource allocation accuracy is low
Solution Approach 1:
The system implements feedback mechanisms by collecting real-time resource usage data and performance metrics, then using this feedback to dynamically adjust resource allocation decisions through the reinforcement learning model, improving accuracy while maintaining manageable complexity
Solution Approach 2:
The patent replaces traditional mechanical/algebraic resource allocation algorithms with a neural network-based reinforcement learning system that learns optimal allocation strategies through interaction with the environment, achieving higher accuracy without proportionally increasing implementation complexity
2Measurement precision
If resource allocation is based on manual configuration, then control precision is high, but labor cost is high
Solution Approach 1:
The system enables self-service by implementing automated resource allocation through reinforcement learning, where the system independently learns and executes optimal allocation decisions without requiring manual configuration, thereby maintaining high control precision while eliminating labor costs
Solution Approach 2:
The patent substitutes manual configuration processes with an intelligent reinforcement learning system that automatically learns optimal resource allocation policies, achieving both high precision and automation
3Productivity
If resource allocation is dynamic and adaptive, then resource utilization efficiency is improved, but system complexity increases
Solution Approach 1:
The system implements dynamic resource allocation by using reinforcement learning to continuously adapt allocation decisions based on changing conditions, improving resource utilization efficiency while the learned policies help manage the inherent complexity
Solution Approach 2:
The system uses real-time feedback from resource usage monitoring to dynamically adjust allocations, improving utilization efficiency through adaptive decision-making that responds to actual system state
Data Source
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AI summary
This application discloses a resource allocation method and an apparatus, and relates to the field of data storage. The method includes: A processor outputs a first model based on a page resource allocated to each cache object and a data read hit ratio of the cache object, where the page resource allocated to each cache object is from a memory pool provided by a storage system. The first model indicates a page resource that needs to be allocated to the cache object when a specific hit ratio is met. The processor outputs a second model based on the first model corresponding to each cache object, where the second model indicates a target page resource to be allocated to each cache object. The processor adjusts, based on the second model, the page resource allocated to each cache object. The processor adjusts the page resource of the cache object based on the second model. In this way, that the processor evenly allocates or evicts the page resource of the cache object is avoided, utilization and allocation rationality of the page resource in the memory pool are improved, and a service processing delay is reduced.