Multi-Level Adaptive Caching for Web Asset Latency
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current cache systems in asset-based web systems face challenges in managing network latency and data access efficiency across geographically distributed locations, particularly in scenarios where multiple devices access shared assets for both read and write operations.
Innovation Solution
A multi-level adaptive caching system that migrates asset data between a back-end cache and local caches based on the number of client devices requesting access and their access privilege types, optimizing data placement to minimize network latency by moving data to the client device for single access scenarios and to the back-end cache for multiple access scenarios.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If asset data is cached at multiple levels (back-end cache and local caches), then data access efficiency is improved, but system complexity increases
Solution Approach 1:
The caching system is segmented into multiple hierarchical levels: a back-end cache and multiple distributed local caches. This segmentation allows different parts of the system to serve different functions - the back-end cache handles centralized management while local caches handle distributed access, thereby improving overall data access efficiency without overwhelming any single component.
Solution Approach 2:
The patent introduces a cache manager as an intermediary component that mediates between the back-end cache and local caches. This intermediary handles the complexity of data migration decisions, coordination, and communication, allowing the system to maintain multiple caching levels while managing the operational complexity through a dedicated control layer.
2Speed
If asset data is migrated to local caches for single device access, then network latency is reduced, but data availability for multiple devices deteriorates
Solution Approach 1:
The system dynamically determines the optimal cache placement by monitoring access patterns and device counts in real-time. When a single device accesses data, the system dynamically migrates it to that device's local cache for faster access. When multiple devices access the same data, the system dynamically relocates it to the back-end cache to ensure availability for all devices. This dynamic adaptation resolves the contradiction between speed and reliability.
Solution Approach 2:
The cache manager continuously monitors access requests and device counts, using this feedback to make informed migration decisions. The feedback loop ensures that data is placed where it will have the greatest impact - either at local caches for single-device speed optimization or at the back-end cache for multi-device availability - thereby resolving the trade-off between access speed and data availability.
3Loss of time
If asset data is migrated between caches based on access patterns, then network latency is minimized, but migration overhead increases
Solution Approach 1:
The caching system implements self-service by automatically monitoring access patterns and making migration decisions without external intervention. The cache manager autonomously analyzes device counts and access requests, then autonomously executes data migrations to optimize latency. This self-service mechanism reduces the need for manual control and minimizes the overhead of migration coordination by allowing the system to self-optimize based on real-time conditions.
Data Source
AI summary
A server monitors receipt of application access requests for application asset data from client devices. Each client device includes a local cache and the server includes a back-end cache. In response to receipt of each application access request, a number of client devices requesting access to the application asset data and an access privilege type requested by each requesting client device are determined. The application asset data is migrated between the back-end cache and at least one local cache based upon the determined number of client devices requesting access to the application asset data and the access privilege type requested by each requesting client device.