Look Ahead Caching for Personalized Web Content
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Solution Overview
Problem
Existing caching mechanisms fail to improve performance for first-time access to personalized web content and require re-caching when user profiles change, leading to latency issues.
Innovation Solution
A system and method for look ahead caching that utilizes CPU cycles to pre-deliver personalized web content to a cache before user access, leveraging the time between server response and user perception, and off-loads caching to underutilized external systems when internal resources are exhausted.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If traditional caching mechanisms are used, then retrieval time for previously accessed content is reduced, but performance for first-time access to personalized web content is not improved and latency increases
Solution Approach 1:
The system performs preliminary caching actions by predicting which personalized web content the user is likely to access next and caching that content in advance during idle periods. This preliminary action ensures that when the user actually requests the content, it is already available in the cache, eliminating latency for first-time access while maintaining consistent performance across all content types
2Ease of operation
If sophisticated rules and procedures are implemented for personalization, then user experience is improved, but query delay increases
Solution Approach 1:
The system pre-processes and caches personalized content based on user profiles and predicted access patterns before the user actually requests it. By performing the sophisticated personalization queries in advance during idle time, the system maintains high user experience quality while eliminating query delays during actual content access
Solution Approach 2:
The system dynamically adjusts the level of personalization and caching strategy based on real-time conditions such as server load, user behavior patterns, and resource availability. This dynamic approach allows the system to maintain sophisticated personalization when resources are available while reducing processing overhead when resources are constrained, thus balancing user experience quality with response time
3Loss of time
If look ahead caching is implemented, then latency is reduced for first-time access, but resource capability utilization becomes a constraint
Solution Approach 1:
The system dynamically monitors resource capability utilization and adjusts the look ahead caching aggressiveness accordingly. When resources are abundant, the system performs more extensive pre-caching to maximize latency reduction. When resources are constrained, the system reduces caching activity to avoid overloading the system. This dynamic adjustment ensures optimal balance between latency reduction and resource utilization
Solution Approach 2:
The look ahead caching system operates autonomously by monitoring its own resource utilization and self-adjusting its caching behavior. The system uses idle resource cycles to perform caching operations without requiring external intervention or dedicated resources, effectively utilizing otherwise wasted computational capacity to reduce latency
Data Source
AI summary
The present invention is a method and system for look ahead caching of personalized web content based upon resource capability. Personalized web content may be delivered to a cache before the web pages are accessed by the user by optimally using the application systems CPU cycles or optionally off-loading the caching to an external system. The system and method of the present invention may employ a resource manager to monitor server usage and off-load the caching process to another dedicated system that may be currently under utilized, while making use of the time period between server response and the actual time the response is seen by the user (network time) and the user think time available for the server.