Preemptive Caching Based on End-User Cues
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Solution Overview
Problem
Navigating web pages can be tedious due to network latency and delays as content only loads when a user interacts with it, degrading the user experience.
Innovation Solution
A system that detects end-user cues, such as gaze or interaction patterns, to predict user intent and preemptively caches additional content, reducing network latency by loading it in the background without changing the current content display.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If content is loaded only when user interacts with it, then network bandwidth is conserved, but network latency and load times increase
Solution Approach 1:
The system performs preliminary actions by detecting user cues (gaze, hover, scrolling) and preemptively caching additional content before the user actually requests it. This anticipatory caching reduces network latency when the user interacts with the content, while still conserving bandwidth by only caching content that is likely to be requested.
2Loss of time
If additional content is preemptively cached, then network latency is reduced, but system resources are consumed
Solution Approach 1:
The system applies partial action by selectively caching only the additional content that is most likely to be requested based on user cues, rather than caching all possible content. This approach reduces network latency for anticipated content while minimizing consumption of system resources.
3Ease of operation
If user intent is predicted and caching action is taken, then user experience is enhanced, but device complexity increases
Solution Approach 1:
The system implements self-service by using sensor data from the user device (gaze detection, touch sensors, scrolling behavior) to automatically predict user intent and trigger caching actions without requiring additional external systems or complex infrastructure. The existing sensor data is leveraged to enhance user experience while minimizing increases in device complexity.
Data Source
AI summary
Systems, methods, and computer-readable media are provided for performing a caching action based on end-user cues. An indication corresponding to the intent of a user is initially detected at a sensor associated with a display providing content. Based on the indication and historical information, the intent of the user is predicted. A caching action corresponding to additional content is provided based on the intent of the user. For example, the caching action may be to preemptively cache the additional content. Alternatively, the caching action is to cease preemptively caching the additional content.