Selective Network Prefetching via Cachability Measures
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Solution Overview
Problem
Uninformed prefetching in network communications can lead to performance decreases and unwanted side effects, such as data loss or unauthorized data posting, due to the lack of selective and intelligent prefetching mechanisms.
Innovation Solution
A system that selectively prefetches content over a network by determining a cachability measure and a prefetchability measure for content objects, using a weighted sum of probabilities based on previous requests, user authorization, network metrics, and annotations, to decide whether to prefetch and where to cache content, minimizing changes to websites and ensuring secure, intelligent prefetching.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If content is prefetched without selective mechanisms, then network performance may be improved through preloading, but unwanted side effects occur such as data loss or unauthorized data posting
Solution Approach 1:
The system performs preliminary actions by determining cachability measures and prefetchability measures before actually prefetching content. This preliminary assessment ensures that only appropriate content is prefetched, preventing unauthorized operations while still achieving performance benefits through preloading of suitable content.
Solution Approach 2:
The system uses feedback mechanisms by analyzing previous requests, user authorizations, network metrics, and annotations to dynamically adjust prefetching decisions. This feedback loop ensures that prefetching behavior adapts to actual usage patterns and security requirements, preventing harmful side effects while maintaining performance optimization.
2Reliability
If selective prefetching mechanisms are implemented with multiple criteria, then data security is improved, but system complexity increases
Solution Approach 1:
The system segments the prefetching decision process into distinct components: determining cachability measures based on previous requests and annotations, determining prefetchability measures based on user authorization and network metrics, and making the final prefetching decision. This segmentation makes the complex system more manageable and maintainable while preserving security benefits.
3Measurement precision
If cachability measures are determined based on multiple factors, then prefetching accuracy is improved, but processing time increases
Solution Approach 1:
The system applies partial action by determining cachability measures and prefetchability measures as separate, independent assessments rather than requiring complete analysis of all factors simultaneously. This allows the system to make progress on prefetching decisions without waiting for complete information, reducing processing time while maintaining measurement accuracy.
Data Source
AI summary
A method, system, an apparatus are directed towards selectively prefetching content over a network. A request for a content object is received. The content object may comprise a link to another content object. A cachability measure for the link may be determined based on whether a plurality of previous requests for the link returned the other content object, an annotation in a link map, a probability of traversing the link, a network metric, or the like. A prefetchability measure for the link may be determined based on the cachability measure and/or another factor relating to the link. The other factor may be an annotation of the link indicating that caching the other content object will cause a related object to be uncachable. Based on the prefetchability measure, the other content object is selectively prefetched for subsequent provisioning and/or display.