Video Cache Progress Control for Lag and Bandwidth Balance
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Solution Overview
Problem
Existing video caching methods struggle to balance the length of cached video content, leading to resource waste, increased costs, and playback lags due to network instability, with existing dynamic methods lacking accuracy in adapting to fluctuating network conditions.
Innovation Solution
A video caching method that predicts user viewing duration and network speed using a play duration prediction model, adjusting cache progress based on video bit rate, lag data, and estimated network speed to optimize cache duration and reduce waste.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If video caching length is increased to prevent playback lags, then playback stability is improved, but cache resource waste and costs increase
Solution Approach 1:
The patent implements dynamic cache progress adjustment based on real-time network speed measurements and predicted viewing duration. The system continuously monitors network conditions and adapts the cache progress accordingly, transitioning from static to dynamic cache management that balances playback stability with resource efficiency.
Solution Approach 2:
The patent changes the cache progress parameter dynamically based on network speed and viewing duration predictions. By adjusting the cache progress parameter in response to varying network conditions and user behavior patterns, the system optimizes the balance between maintaining playback stability and reducing cache resource waste.
2Reliability
If video caching length is increased to ensure smooth playback, then playback quality is improved, but bandwidth consumption increases
Solution Approach 1:
The patent implements a feedback mechanism that monitors actual network speed and compares it with predicted values. Based on this feedback, the system adjusts cache progress to match actual network capabilities, preventing excessive bandwidth consumption while ensuring smooth playback quality.
Solution Approach 2:
The patent uses predicted viewing duration to determine how much video to cache in advance. By predicting user behavior patterns and pre-loading appropriate video segments, the system prepares content ahead of time without wasting bandwidth on content that may not be viewed.
3Loss of energy
If dynamic cache adjustment is implemented to reduce waste, then cost efficiency is improved, but system complexity increases
Solution Approach 1:
The patent implements self-service mechanisms where the system automatically monitors network conditions, predicts viewing duration, and adjusts cache progress without requiring manual intervention. The system serves itself by making intelligent decisions about caching based on real-time data and learned patterns.
Solution Approach 2:
The patent replaces complex manual cache management mechanisms with automated algorithms that use machine learning models for prediction and intelligent control logic. This substitution reduces operational complexity while improving cost efficiency through automated optimization.
4Loss of energy
If cache progress is dynamically adjusted to match network conditions, then resource efficiency is improved, but cache policy accuracy requirements increase
Solution Approach 1:
The patent uses predicted viewing duration to determine cache progress, which may be slightly conservative (partial action) or aggressive (excessive action) depending on network conditions. This partial or excessive action approach allows the system to adapt to varying accuracy requirements while maintaining resource efficiency.
Data Source
AI summary
Embodiments of the present disclosure provide a video caching method and device. The method obtains a video bit rate corresponding to a video to be cached, lag data of a plurality of downloaded videos, an estimated network speed value and a first estimated viewing duration, wherein the first estimated viewing duration is obtained based on a current play progress of the video to be cached, and the estimated network speed value is determined based on network speed values of a plurality of pieces of downloaded data during download. A target cache progress of the video to be cached is determined according to the video bit rate, the lag data, the estimated network speed value and the first estimated viewing duration, and a cache progress of the video to be cached is controlled according to the target cache progress.