Variable Sampling Rate Mechanism for Website Traffic Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional sampling mechanisms for website visitation analysis fail to provide sufficient resolution for normal traffic days while handling high-traffic spikes, leading to system overloads and inadequate data sets.
Innovation Solution
A variable sampling rate mechanism that adjusts based on target sample numbers and baseline rates, dynamically resampling data during high-traffic periods to maintain appropriate data set sizes and prevent system overload.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a fixed sampling rate is used for normal traffic days, then sufficient resolution is maintained for normal traffic analysis, but system overload occurs during high-traffic spikes
Solution Approach 1:
The patent implements dynamic sampling rate adjustment based on real-time traffic conditions. The system monitors traffic volume and automatically switches between a first sampling rate for normal traffic and a second sampling rate for high-traffic periods, resolving the contradiction between maintaining measurement precision and ensuring system stability.
2Reliability
If a lower sampling rate is used to handle high-traffic days, then system overload is prevented, but data resolution becomes insufficient for normal traffic days
Solution Approach 1:
The system dynamically adjusts the sampling rate based on traffic conditions, using a lower sampling rate during high-traffic periods to prevent system overload while maintaining a higher sampling rate during normal periods to ensure sufficient data resolution for analysis.
3Quantity of substance
If a higher sampling rate is used during high-traffic periods, then adequate data is captured for spike analysis, but system performance deteriorates due to processing overload
Solution Approach 1:
The patent implements conditional sampling rate adjustment that increases the sampling rate during high-traffic periods to capture adequate data for spike analysis, while decreasing the sampling rate during normal periods to maintain system processing efficiency and prevent overload.
Data Source
AI summary
A data set containing website traffic data or other data is sampled according to a variable sample rate. A target number of samples per time period is established, and a baseline sample rate is determined. Data items in the data set are sampled according to the baseline sample rate, to obtain a sample set. For time periods where the size of the resulting sample set exceeds the target number of samples, a new sample rate is established and the data items for the time period are resampled. Appropriate sampling capability can thus be provided for website traffic in normal time periods, while maintaining capability for handling spikes and other variations in website traffic as may take place in response to certain periodic or non-periodic events.