Browser Inference Module Prioritizes Content Processes Over Ads
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Solution Overview
Problem
Existing information handling systems face performance issues due to the overwhelming presence of advertisements on webpages, which slows down the system's ability to process and display desired content effectively.
Innovation Solution
An information handling system that includes a web browser, a hardware scheduler, and a browser inference module. The browser inference module uses machine learning to provide indications to the hardware scheduler to prioritize processes associated with content over those associated with advertisements, based on browser process information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If advertisements are loaded and processed alongside content, then the webpage can display advertising content, but the system performance and content delivery speed deteriorate
Solution Approach 1:
The patent segments webpage content into distinct categories: content processes and advertisement processes. The browser inference module analyzes browser process information to identify and separate these process types, allowing the hardware scheduler to apply different prioritization strategies to each segment, thereby improving content delivery speed despite the presence of multiple processes
Solution Approach 2:
The patent applies local quality by assigning different priority levels to different types of processes based on their function. Content-related processes are assigned high priority for immediate execution, while advertisement processes are assigned low priority. This differential treatment ensures that critical content delivery is not hindered by the presence of advertisement processes
2Productivity
If all processes are treated equally by the scheduler, then the system maintains simple scheduling logic, but content delivery performance deteriorates due to advertisement processes consuming resources
Solution Approach 1:
The patent introduces a browser inference module as an intermediary between the browser and the hardware scheduler. This intermediary analyzes browser process information, identifies content versus advertisement processes, and provides prioritization recommendations to the scheduler. This approach enables intelligent scheduling without requiring complex modifications to the scheduler itself
Solution Approach 2:
The system implements feedback by having the browser inference module continuously monitor browser process information and dynamically adjust scheduling priorities based on real-time conditions. The module receives information about running processes and provides ongoing prioritization guidance to the hardware scheduler, ensuring content processes receive appropriate resources
Data Source
AI summary
An information handling system includes processing hardware, a web browser, a hardware scheduler, and a browser inference module. The web browser retrieves a webpage including content and an advertisement, and provides browser process information related to the processes launched by the web browser for the content and the advertisement. The hardware scheduler directs the execution of processes on the processing hardware. The browser inference module receives the browser process information, and provides an indication to the hardware scheduler to prioritize first processes associated with the content over second processes associated with the advertisement based upon the browser process information.