Predictive Data Pre-fetching for Webpage Loading Latency
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The retrieval of user-specific information from webpages can be time-consuming, leading to prolonged webpage loading times, which frustrates users who regularly access the same information at specific times.
Innovation Solution
A predictive analysis apparatus that uses a processor to generate predictions of user login times and probabilities, pre-fetching and pre-generating data for cache storage, taking into account user history, calendar events, location, and overrides for special conditions like holidays or traffic, to ensure timely and updated data availability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data is retrieved from multiple resources when user logs in, then accurate user information is obtained, but webpage loading time increases significantly
Solution Approach 1:
The system performs preliminary actions by predicting user login times based on historical behavior patterns and pre-fetching required data from multiple resources before the user actually logs in. This eliminates the need to retrieve data during the login moment, thus maintaining data accuracy while avoiding loading delays.
Solution Approach 2:
The system serves itself by automatically monitoring user behavior patterns, generating predictions, and pre-fetching data without manual intervention. The predictive analytics engine continuously learns from user login patterns and autonomously optimizes data retrieval timing, resolving the contradiction between data accuracy and loading speed.
2Speed
If data is pre-fetched based on user behavior patterns, then webpage loading speed improves, but system complexity increases due to predictive analytics requirements
Solution Approach 1:
The predictive analytics system is self-configuring and self-optimizing, automatically learning user patterns and adjusting predictions without requiring complex manual configuration. This reduces operational complexity while maintaining high data retrieval speeds through intelligent automation.
Solution Approach 2:
The system incorporates feedback loops where prediction accuracy is continuously monitored and used to refine future predictions. This self-correcting mechanism improves speed over time while keeping system complexity manageable through automated optimization rather than manual tuning.
Data Source
AI summary
One or more non-transitory computer-readable media storing computer-executable instructions which, when executed by a processor on a computer system, perform a method for predictive analysis for determining which data to pre-fetch at a specific point in time. The method may include generating a prediction corresponding to a user login to a webpage. The prediction may include a user identification, a start time, an end time, and a probability of user login. The method may also include pre-generating and pre-fetching, in response to the prediction, data for at least part of a user login webpage. The method may also include storing the data in a cache memory. The method may also include updating the data stored in the cache memory.