Cloud Cache Management via Crowd-Sourced Access Patterns

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Solution Overview

Problem

Modern applications experience suboptimal cache usage due to initial lack of relevant data in caches and frequent updates, leading to prolonged suboptimal performance and degradation of cache memory.

Innovation Solution

Implementing crowd-sourced data intelligence and AI-driven cache management that prioritizes data based on usage patterns from multiple users, generating enhanced cache replacement policies to optimize cache utilization and reduce latency, while avoiding frequent rewrites that degrade cache performance.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If cache replacement policies are enhanced slowly over time by measuring disk access patterns, then cache performance improves gradually, but application performance remains suboptimal for extended periods

Engineering Contradiction:

Improvecache performanceVSAvoidapplication performance

Core Design Contradiction:

ReliabilityVSProductivity

Solution Approach 1:

The system performs preliminary actions by collecting and analyzing disk access patterns from multiple applications before they are actually executed. This allows the cache replacement policy to be pre-configured with accurate data about which data blocks will be frequently accessed, eliminating the warm-up period and providing optimal cache performance from the start of application execution.

Inventive Principle:

Principle #10Preliminary action

2Adaptability or versatility

If applications are updated frequently to improve functionality, then application capabilities are enhanced, but cache usage becomes suboptimal more often

Engineering Contradiction:

Improveapplication functionalityVSAvoidcache usage efficiency

Core Design Contradiction:

Adaptability or versatilityVSReliability

Solution Approach 1:

The system implements a feedback mechanism where disk access patterns are continuously monitored and analyzed. When applications are updated, the system receives feedback about new access patterns and dynamically adjusts the cache replacement policy accordingly. This ensures that the cache remains optimized even as applications evolve and change their data access behaviors through updates.

Inventive Principle:

Principle #23Feedback

3Speed

If cache is used to improve application launch speed, then user experience is enhanced, but cache memory degrades from frequent rewrites

Engineering Contradiction:

Improveapplication launch speedVSAvoidcache memory life

Core Design Contradiction:

SpeedVSDuration of action of stationary object

Solution Approach 1:

The system changes the parameter of cache replacement policy from static or simple algorithms to dynamic policies based on analyzed disk access patterns. By identifying which data blocks will be frequently accessed and rewriting them, the system optimizes cache utilization to store only the most valuable data. This reduces unnecessary cache rewrites and extends cache memory life while maintaining fast application launch performance.

Inventive Principle:

Principle #35Parameter changes

Data Source

PatentUS10990531B2Cloud-based frequency-based cache management

Publication Date: 2021.04.27 INTEL CORP

AI summary

Systems, apparatuses and methods may provide for technology that in response to one or more of an installation of an application or a modification to the application, generates a lookup key based on a first file that is associated with the application, determines that the lookup key is to be transmitted to a server, and determines whether to store at least a portion of the first file in a memory cache based on a first frequency indicator associated with the first file from the server.