Compressed Data Update Using Partial Decompression Deltas
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Solution Overview
Problem
Existing data update methods in communication systems face inefficiencies and inaccuracies due to the use of universal compression and decompression methods, leading to increased bandwidth consumption and prolonged update times, especially in scenarios where different terminals use varying compression techniques.
Innovation Solution
A data update method involving partial decompression and re-compression of compressed data using specific compression and decompression methods, allowing for accurate determination of differential data without full decompression, thereby improving update efficiency and accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data is synchronized in real-time across all terminals, then data consistency is improved, but network traffic consumption increases and terminal power is consumed excessively
Solution Approach 1:
The patent applies local quality by differentiating synchronization strategies based on data types and terminal characteristics. Different terminals receive different synchronization frequencies and data subsets based on their roles (e.g., primary vs. secondary terminals) and data importance, rather than uniform real-time synchronization to all terminals.
Solution Approach 2:
The patent implements periodic action through scheduled synchronization intervals and batch updates. Instead of continuous real-time synchronization, data is synchronized at predetermined intervals or when specific thresholds are met, reducing network traffic and power consumption while maintaining acceptable consistency levels.
2Reliability
If data is synchronized in real-time across all terminals, then data consistency is improved, but network traffic consumption increases
Solution Approach 1:
The patent applies local quality by differentiating synchronization strategies based on data types and terminal characteristics. Different terminals receive different synchronization frequencies and data subsets based on their roles (e.g., primary vs. secondary terminals) and data importance, rather than uniform real-time synchronization to all terminals.
Solution Approach 2:
The patent implements periodic action through scheduled synchronization intervals and batch updates. Instead of continuous real-time synchronization, data is synchronized at predetermined intervals or when specific thresholds are met, reducing network traffic and power consumption while maintaining acceptable consistency levels.
3Loss of information
If data update frequency is increased, then data freshness is improved, but power consumption increases
Solution Approach 1:
The patent applies partial action by updating only the necessary subset of data for each terminal rather than all data. Critical data is updated more frequently while less critical data is updated less frequently, optimizing the balance between data freshness and power consumption.
Solution Approach 2:
The patent changes synchronization parameters dynamically based on data importance, terminal type, and network conditions. Update frequency, data subsets, and synchronization thresholds are adjusted as parameters to optimize both data freshness and power consumption.
Data Source
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AI summary
This application discloses a data update method and apparatus, a device, and a computer-readable storage medium, and relates to the field of communication technologies. The method includes: obtaining first data obtained by compressing third data in at least a first compression manner and a second compression manner successively, and second data obtained by compressing fourth data in at least the first compression manner and the second compression manner successively, where the fourth data is obtained by updating the third data; decompressing the first data and the second data in a first decompression manner corresponding to the second compression manner to obtain first intermediate data and second intermediate data; determining first differential data between the second intermediate data and the first intermediate data; and updating the first data based on the first differential data and the first intermediate data. In this application, the first differential data is accurately determined based on the first intermediate data and the second intermediate data that are obtained through partial decompression, and the first data can be efficiently updated based on the first differential data and the first intermediate data.