Rule-Based Data Compression for Narrowband IoT Overhead Reduction
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Solution Overview
Problem
Existing data compression and decompression technologies for narrowband IoT devices face challenges in reducing data size to minimize storage and transmission overheads, especially with increasing power consumption and data scale demands.
Innovation Solution
A data compression and decompression method utilizing customizable matching rules that include preset fields, matching rules, and compression/decompression actions to selectively send or restore data based on specific criteria, allowing for flexible and precise data handling.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If packet header compression (ROHC) is used to compress unchanged parts of data, then transmission overhead is reduced, but the compressed data size remains relatively large
Solution Approach 1:
The patent segments data into multiple granularities including packets, fields, and bits. It applies compression at different levels: packet-level compression for header information, field-level compression for repeated field patterns, and bit-level compression for individual bit sequences. This multi-level segmentation enables more aggressive compression while maintaining data integrity.
Solution Approach 2:
The patent implements nested compression structures where compression contexts are embedded within each other. A packet compression context contains field compression contexts, which in turn contain bit-level compression patterns. This nested structure allows cumulative compression effects where each level builds upon the previous level's compression results.
2Quantity of substance
If dictionary compression or statistical compression algorithms are used, then data compression is achieved, but the compressed data size is still relatively large
Solution Approach 1:
The patent employs dynamic compression contexts that adapt to the actual data patterns being compressed. Rather than using static dictionary entries, the system dynamically identifies and learns compression patterns from the input data stream, adjusting compression strategies in real-time based on observed data characteristics and frequency distributions.
Solution Approach 2:
The patent changes compression parameters such as context window sizes, compression thresholds, and encoding strategies based on data characteristics. It dynamically adjusts these parameters to optimize compression ratios for different data types and patterns, transitioning between different compression modes as needed.
3Quantity of substance
If existing compression methods are used for NB-IoT devices, then some data reduction is achieved, but power consumption remains high and standby time is limited
Solution Approach 1:
The patent performs preliminary compression of data before transmission, reducing the amount of data that needs to be sent over the network. It also pre-establishes compression contexts and patterns that can be reused across multiple transmissions, avoiding the need to re-analyze data patterns for each individual transmission event.
Solution Approach 2:
The patent maintains continuous compression contexts across multiple data transmissions, allowing the compression algorithm to build upon previously learned patterns. This continuity enables the system to achieve better compression ratios over time as it accumulates knowledge about data patterns, reducing the energy cost per transmission.
Data Source
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AI summary
A data compression method and a data decompression method for an electronic device, and an electronic device are provided, to make compressed data become smaller, so that overheads caused by data storage and receiving/sending are reduced. The method is: Each of one or more matching rules includes one or more matching entries, each matching entry is used to perform matching on one or more pieces of to-be-matched data in a to-be-matched data group, and each matching entry includes: a preset field; a matching rule field, used to indicate to perform matching between first data in to-be-matched data and the preset field according to a specific rule; and a compression rule field, used to indicate, based on a matching result that is obtained through matching by using the matching rule field, that data is not to be sent or that one or more bits are to be sent. The method is specifically: receiving a to-be-matched data group (201), obtaining a target matching rule by performing matching based on the preset field and the matching rule field in each matching entry in the one or more matching rules (202), and performing processing based on a compression rule field in each matching entry in the target matching rule (203).