Column-Wise Entropy Coding for Continuous Fixed-Length Data Compression
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Solution Overview
Problem
Existing data compression techniques are inefficient for fixed-length data in sensor networks, leading to suboptimal compression efficiency and increased data transfer volumes, as they do not effectively handle the continuous transmission of fixed-length records without significant accumulation time, which can cause delays.
Innovation Solution
A data compression coding method that divides fixed-length bit strings into columns of predetermined bit width, determines the probability of bit values within each column, and applies entropy coding based on these probabilities, allowing for continuous compression and decoding of sensor data without relying on field boundaries.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If existing data compression techniques are used for fixed-length sensor data, then data transfer volume is reduced, but compression efficiency is suboptimal and delays occur due to accumulation requirements
Solution Approach 1:
The fixed-length data string is divided into multiple columns based on bit position, allowing independent probability calculation and entropy coding for each column. This segmentation enables more efficient compression by exploiting statistical patterns within each column position across multiple records, resolving the contradiction between maintaining fixed-length structure and achieving high compression efficiency.
2Productivity
If data is accumulated for compression, then compression efficiency improves, but transmission delays increase
Solution Approach 1:
The entropy coding process operates continuously on incoming fixed-length records without requiring significant accumulation time. By calculating probabilities and performing entropy coding column by column as data arrives, the system maintains continuous compression operation, achieving high compression efficiency while minimizing transmission delays.
3Ease of operation
If fixed-length data structure is maintained, then data format simplicity is preserved, but compression efficiency decreases
Solution Approach 1:
The invention transforms the compression approach from row-based (processing each fixed-length record as a whole) to column-based (processing bits at the same position across multiple records). This dimensional change allows the system to maintain the simple fixed-length data structure while achieving superior compression efficiency through statistical analysis across the new dimension.
Data Source
AI summary
A compression coding method, apparatus, and program suitable for continuously coding pieces of fixed length data are provided. The compression coding method includes: dividing, into columns each with a predetermined bit width, records consisting of a fixed-length bit string that includes one or more fields, pieces of data of the same type being contained in the same field among fields determined in advance; and determining, for each column, a probability of occurrence of a bit value in the column at the same position among a plurality of records, and coding the plurality of records on the basis of the probability of occurrence using an entropy coding method.