Client Assistant Predicting User Actions to Reduce Latency
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
There is a significant latency between a user clicking on a hyperlink and the document being rendered in a web browser, which can be attributed to the time taken to download and render the document, and this latency is not efficiently reduced by existing technologies.
Innovation Solution
A client assistant is implemented on the client computer to predict the user's next document selection by monitoring browsing activities and preloading or prefetching the document from the client cache or server, using content differences to update stale versions, thereby reducing the latency by initiating document retrieval before the user's mouse-up action.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If the web browser waits for user click before downloading documents, then user control is maintained, but document rendering latency increases
Solution Approach 1:
The system performs preliminary actions by monitoring mouse movements and predicting the next hyperlink the user will click, then proactively initiating document downloads before the actual click occurs. This prefetching mechanism reduces rendering latency by having documents ready in advance, while still respecting user control by only downloading documents that are predicted to be requested based on actual mouse behavior patterns.
2Productivity
If the client assistant monitors and predicts user browsing activities, then document retrieval speed improves, but system complexity increases
Solution Approach 1:
The client assistant implements self-service by automatically monitoring mouse movements, predicting user intentions, and initiating document downloads without requiring explicit user commands. The system serves itself by using the browser's own resource tracking capabilities to make predictions and execute prefetching operations, reducing the need for complex external intervention while improving retrieval speed.
Solution Approach 2:
The system employs feedback mechanisms by continuously monitoring actual user mouse movements and comparing them against predicted selections. This feedback loop allows the client assistant to refine its prediction algorithms and adjust its prefetching behavior, improving accuracy over time while managing system complexity through iterative optimization rather than requiring overly complex initial designs.
3Duration of action of moving object
If the client assistant preloads documents from server, then rendering time decreases, but network bandwidth consumption increases
Solution Approach 1:
The system applies partial action by selectively prefetching only the portion of documents that are most likely to be needed based on mouse movement predictions, rather than loading entire documents or all possible documents. This targeted approach reduces unnecessary bandwidth consumption while still achieving significant rendering time improvements for the predicted documents.
Data Source
AI summary
A client assistant, sometimes called a browser helper, runs on a client computer. The client assistant monitors a user's browsing activities and infers one or more next documents that are most likely to be requested by the user. The client assistant attempts to locate a fresh copy of the inferred next document within a client cache. If a fresh copy of the inferred document is not found in the client cache, the client assistant submits a document download request to a document server.