Dynamic Cache Data Management via Hierarchical Segmentation
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Solution Overview
Problem
Conventional data caching systems cache all data since user login, leading to irrelevant data storage, heavy memory and processing burdens, and slow turnaround times due to inability to determine data relevancy or caching duration, and lack of cross-channel data transformation.
Innovation Solution
A dynamic management system for stored cache data using proactive processors and usage monitor engines to construct adapted hierarchical cache data objects, selectively caching and pre-populating data based on predictive usage patterns, with improved indexing and time-to-live parameters for efficient data retrieval and reduction of obsolete data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional systems cache all data since user login, then data availability is improved, but memory burden and processing load increase significantly
Solution Approach 1:
The patent segments cached data into hierarchical levels (L1 cache, L2 cache, L3 cache) with different retention periods and access frequencies. Instead of caching all data uniformly, the system divides data into relevant and irrelevant portions, caching only relevant data at each hierarchical level with progressively shorter retention periods, thereby reducing memory burden while maintaining data availability for frequently accessed information
Solution Approach 2:
The system applies different caching strategies to different data types and users based on their specific needs and usage patterns. Each user receives customized cache content based on their profile, device type, and historical behavior, rather than a uniform caching approach. This local optimization reduces overall memory consumption by allocating cache resources only where they provide value
2Reliability
If conventional systems cache all data since user login, then data completeness is improved, but processing load increases significantly
Solution Approach 1:
The system performs preliminary actions by pre-fetching and caching only the data that will be needed based on predictive analytics of user behavior patterns. Instead of waiting for users to request data and then processing retrieval requests for potentially irrelevant information, the system proactively identifies and caches relevant data in advance, reducing the processing load during actual user interactions while maintaining data completeness for predicted needs
Solution Approach 2:
The patent dynamically changes caching parameters such as retention time, cache size, and refresh frequency based on data relevance, user activity patterns, and system load conditions. This adaptive parameter adjustment optimizes processing load by reducing cache invalidation and refresh operations for irrelevant data while ensuring complete and up-to-date caching for relevant information
3Reliability
If conventional systems cache irrelevant data over extended time periods, then data availability for potential future use is improved, but memory burden increases
Solution Approach 1:
The system implements dynamic cache management where retention periods and cache validity are continuously adjusted based on actual usage patterns, user feedback, and changing relevance. Instead of static long-term caching of all data, the system dynamically extends or shortens cache retention for different data elements, maintaining availability for data that proves useful while automatically expiring irrelevant data to free memory resources
4Reliability
If immense amounts of data are cached, then data completeness is improved, but turnaround time for searching and fetching relevant data increases
Solution Approach 1:
The patent segments the cache into hierarchical levels with different scopes and optimization goals. L1 cache contains highly relevant, frequently accessed data for immediate retrieval; L2 cache contains moderately relevant data with longer retention; L3 cache contains less frequently accessed data. This segmentation enables the system to maintain data completeness across all levels while achieving fast turnaround times by serving most requests from optimized L1 and L2 caches, avoiding the need to search through immense amounts of data in a single undifferentiated cache
Data Source
AI summary
Embodiments of the invention are directed to systems, methods and computer program products structured for dynamic management of stored cache data based on usage information. The invention is structured for light-weight granular data caching based on construction of adapted hierarchical data objects with improved indexing, for reducing memory and processing burdens on data caching servers and reducing turnaround time for activity execution. Specifically, the invention is configured to trigger, via the proactive processor, retrieval of truncated technology data for caching from a usage database based on the adapted truncated cache data retrieval command; and construct a plurality of adapted hierarchical cache data objects, for each of the plurality of users, and cache the constructed plurality of adapted hierarchical cache data objects, for each of the plurality of users, in the distributed cache layer in a distributed cache layer.