Time-Dependent Prefetch Hinting for Faster Web Page Rendering
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Solution Overview
Problem
Existing web page loading techniques lack efficiency in optimizing resource prefetching based on time-dependent factors, leading to suboptimal loading times and user experience.
Innovation Solution
Implementing time-dependent, machine-generated hints that utilize resource samples collected over time to compute probabilities for resource usage, enabling optimized prefetching and improved loading times by predicting resource needs based on historical data and temporal trends.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If traditional web page loading techniques are used, then the system is simple to implement, but the page load time is increased and resource prefetching is suboptimal
Solution Approach 1:
The patent implements preliminary action by collecting resource samples and computing time-based probabilities in advance, before actual web page loading occurs. The hinting machine pre-processes resource usage data and generates time-dependent probability functions that can be quickly applied during actual page loads, eliminating the need for complex real-time analysis during the critical loading phase.
Solution Approach 2:
The patent introduces a hinting machine as an intermediary component between the web server and the client browser. This intermediary collects resource samples, computes time-based probabilities, and generates hints that guide the client's resource fetching behavior. The intermediary handles the computational complexity separately, allowing the core web loading system to remain relatively simple while achieving optimized performance.
2Productivity
If time-dependent hinting is implemented, then resource prefetching is optimized, but the device complexity increases due to sample collection and probability computation
Solution Approach 1:
The hinting machine performs self-service by automatically collecting resource samples from ongoing web transactions and autonomously computing time-based probabilities without requiring manual intervention or complex external systems. The system feeds on its own operational data, continuously improving its hinting accuracy while maintaining a manageable complexity level through automated processing.
Solution Approach 2:
The patent implements periodic action by collecting resource samples at regular intervals during web transactions and updating time-based probability functions periodically. This approach allows the system to gather sufficient data for accurate probability computation without continuously monitoring every single resource event, thereby balancing productivity improvement with controlled system complexity.
3Reliability
If external hinting information is unavailable, then the system can operate independently, but the hinting accuracy may be reduced
Solution Approach 1:
The patent implements feedback mechanisms where the hinting machine continuously monitors actual resource usage outcomes and uses this feedback to refine its time-based probability computations. By comparing predicted resource usage patterns with actual observations, the system adapts and improves its accuracy over time, maintaining reliable operation even when external hinting information is unavailable.
Data Source
AI summary
Embodiments seek to improve prefetch hinting using time-dependent, machine-generated hints. Some embodiments operate in context of client machines in communication hinting machines that can develop information about whether and how resources are used in network transactions over time by collecting “resource samples.” Each resource sample can identify rendering status information of a resource at a sample time. The time-based samples can be used to compute time-based probabilities for the resources, indicating, for example, the likelihood of a resource being used to render a web page at some subsequent time. Time-dependent hints can be generated as a function of the time-based probabilities, and the time-dependent hints can be used to improve prefetching by optimizing the hinting information with respect to a particular request time (e.g., the prefetching hints for rendering a web page can be generated in a manner that accounts for when the web page is being rendered).