Cache Data Deletion Scoring Using Device Weight
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current data storage systems face inefficiencies in managing data across different performance tiers, particularly in determining which data chunks to delete from cache systems to optimize storage space while minimizing the cost of re-fetching data from slower storage devices.
Innovation Solution
A method is implemented where a deletion score is calculated for each frontend data chunk based on its corresponding backend data chunk's device weight and access duration, allowing for targeted deletion of data chunks stored on slower devices to free up cache space, thereby optimizing storage system performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If data chunks are deleted from cache system to free up storage space, then cache storage capacity is improved, but data re-fetching cost increases
Solution Approach 1:
The patent applies parameter changes by calculating a deletion score for each data chunk based on multiple parameters including device weight (indicating storage device type) and duration weight (indicating access time). This scoring mechanism transforms the cache management approach from simple LRU to a multi-parameter evaluation system that predicts re-fetching costs and prioritizes deletion of data chunks with lowest deletion scores, thereby balancing cache capacity utilization with minimization of re-fetching operations
Solution Approach 2:
The patent implements preliminary action by pre-calculating device weights for backend storage devices and duration weights for cached data chunks before deletion decisions are needed. These pre-computed parameters are stored and readily available when cache eviction is required, allowing the system to quickly determine which data chunks to delete without performing complex real-time analysis, thus enabling efficient cache management while minimizing re-fetching costs
2Productivity
If data from slower devices is prioritized for deletion, then cache performance is improved, but data loss risk increases
Solution Approach 1:
The patent implements feedback mechanisms by continuously monitoring access patterns and updating duration weights for cached data chunks. The system tracks how long data chunks have been cached and their access frequency, feeding this information back into the deletion score calculation. This feedback loop ensures that data chunks accessed frequently or recently are assigned higher duration weights, making them less likely to be deleted even if they reside on slower devices, thereby maintaining data availability while improving cache management efficiency
Solution Approach 2:
The patent uses parameter changes by dynamically adjusting device weights based on the performance characteristics of different backend storage devices. The system evaluates and assigns weights to storage devices according to their speed and reliability characteristics, and these weights are incorporated into the deletion score calculation. This dynamic parameter adjustment allows the system to adapt to changing storage conditions and maintain optimal balance between cache performance and data availability
Data Source
AI summary
A method, computer program product, and computing system for storing a plurality of frontend data chunks within a cache system. The plurality of frontend data chunks correspond to a plurality of backend data chunks stored within a data array. A device weight is determined for each of the plurality of backend data chunks. The device weight is indicative of the type of storage device upon which each of the plurality of backend data chunks is stored within the data array. A deletion score is assigned to each of the plurality of frontend data chunks. Each deletion score is based, at least in part, upon the device weight determined for its corresponding backend data chunk.