Browser Rendering Engine Optional Resource Detection
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Solution Overview
Problem
The rendering time of web pages is significantly delayed due to the need for browsers to fetch and process numerous embedded resources, many of which are optional and do not affect the content's significance.
Innovation Solution
A system identifies optional embedded resources by comparing rendering results with and without these resources, using a similarity score to determine if they can be skipped, thereby optimizing the rendering process and reducing network bandwidth usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the browser fetches all embedded resources during rendering, then the completeness of the rendered web page is improved, but the rendering time increases significantly
Solution Approach 1:
The patent extracts and identifies optional embedded resources from the web page rendering process. By separating optional resources (those that do not affect content significance) from required resources, the system can selectively skip fetching optional ones, thereby reducing rendering time while maintaining the completeness of essential content.
Solution Approach 2:
The patent performs preliminary analysis of embedded resources before the actual rendering process. By pre-identifying which resources are optional through pattern matching and similarity scoring, the system prepares in advance to skip these resources during rendering, thus avoiding the time cost of fetching and processing them.
2Productivity
If the browser skips optional embedded resources, then the rendering speed is improved, but the accuracy of determining optionality becomes more critical
Solution Approach 1:
The patent implements a feedback mechanism where the rendering engine compares the rendered output with and without optional resources to calculate a similarity score. This feedback loop ensures accurate determination of optionality by verifying that skipping a resource does not significantly affect the rendered content, thus maintaining measurement precision while improving rendering speed.
Solution Approach 2:
The patent changes the parameter of resource identification from binary (fetch or skip) to a continuous similarity score. By calculating how similar the rendered output is with and without each resource, the system achieves more precise determination of optionality, allowing nuanced decisions about which resources to skip based on their actual impact on content significance.
3Measurement precision
If the system analyzes each embedded resource to determine if it is optional, then the accuracy of resource classification is improved, but the processing overhead increases
Solution Approach 1:
The patent segments the analysis process into distinct phases: pattern matching phase (low overhead) and similarity scoring phase (high precision). By dividing resources into groups based on URL patterns first, then applying detailed similarity analysis only to borderline cases, the system achieves accurate classification while managing processing overhead through hierarchical processing.
Solution Approach 2:
The patent applies partial analysis to all resources (pattern matching) and excessive analysis (full similarity scoring) only to resources that fall into gray areas. This selective application of analysis depth ensures that clearly optional or required resources are classified quickly with minimal overhead, while only ambiguous cases receive the full precision treatment.
Data Source
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AI summary
Implementations optimize a browser render process by identifying content neutral embedded items and rendering a web page without fetching the content neutral items. An example method includes identifying a URL pattern common to a plurality of URLs stored in fetch records and selecting a sample of URLs from the plurality. The method also includes, for each URL in the sample, determining whether the URL is optional by generating a first rendering result using content for the URL and a second rendering result without using the content for the URL and calculating a similarity score for the URL by comparing the first rendering result and the second rendering result, the URL being optional when the similarity score is greater than a similarity threshold. The method may also include storing the URL pattern in a data store of optional resource patterns when a majority of the URLs in the sample are optional.