Dynamic Prefetching Model Reduces Latency

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Solution Overview

Problem

Existing web browsing technologies face challenges in reducing latency and improving accuracy in prefetching content, especially in mobile devices where resources such as data, bandwidth, and battery life are limited.

Innovation Solution

Implementing a dynamic prefetching model that predicts user selection based on the relationship between search results and the viewport of the device, using data such as viewport position, orientation, zoom level, and user interactions to assign scores to links and selectively generate prefetch requests.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Loss of time

If prefetching is implemented to reduce latency, then user experience improves, but resource consumption (data, bandwidth, battery) increases

Engineering Contradiction:

ImprovelatencyVSAvoidresource consumption

Core Design Contradiction:

Loss of timeVSLoss of energy

Solution Approach 1:

The system performs preliminary actions by prefetching content before the user actually selects it. The control module predicts which content the user will select next and retrieves it in advance, so that when the user does select it, the content is already available locally, eliminating the latency between selection and display while avoiding unnecessary prefetching of content the user won't actually use.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system uses dynamic user models that continuously adapt and update based on observed user behavior. The prefetching model is not static but dynamically adjusts predictions based on real-time user interactions, device state, and contextual information, allowing it to optimize the balance between prefetching aggressiveness and resource conservation based on current conditions.

Inventive Principle:

Principle #15Dynamics

2Ease of manufacture

If static prefetching models are used, then implementation is simple, but prefetching accuracy is low

Engineering Contradiction:

Improveimplementation simplicityVSAvoidprefetching accuracy

Core Design Contradiction:

Ease of manufactureVSMeasurement precision

Solution Approach 1:

The patent transitions from static prefetching models to dynamic user models that continuously learn and adapt. The control module observes user interactions, device characteristics, and contextual factors in real-time, updating the prefetching predictions dynamically. This allows the system to maintain high accuracy across different users and situations without requiring complex manual configuration or implementation.

Inventive Principle:

Principle #15Dynamics

Data Source

PatentUS12314273B2Prefetching using dynamic user model to reduce latency

Publication Date: 2025.05.27 MICROSOFT TECHNOLOGY LICENSING LLC

AI summary

A device includes a memory that stores a prefetching model. A control module receives a content page including one or more links each associated with selectable content and collects data associated with the content page. The collected data includes at least one of first data indicative of respective relationships between each of the links and a viewport of the device and second data indicative of characteristics of the viewport. The control module further assigns, using the prefetching model, respective scores to each of the links based on the collected data, and selectively generates, based on the assigned scores, a request to prefetch the selectable content associated with at least one of the links.