Packet Payload Compression Using Zero-MSB Byte Grouping
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Solution Overview
Problem
Networks with battery-powered devices and limited radio frequency bandwidths face limitations in data transmission and reception capacity using known technologies.
Innovation Solution
Implementing data compression techniques such as 're-indexing' and 'value-mapping' to reduce the number of most significant bits (MSBs) from packet payloads, along with a packet header that indicates the compression method used, to enhance network throughput and reduce energy consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If data compression techniques are implemented to reduce data size, then network throughput is enhanced and energy consumption is reduced, but device complexity increases
Solution Approach 1:
The patent segments the data stream into fixed-size blocks (e.g., 64-byte blocks) and processes each block independently through the compression algorithm. This segmentation allows the complex compression logic to be applied in manageable, discrete units, reducing the computational burden on battery-powered devices while maintaining effective compression ratios.
Solution Approach 2:
The patent employs lookup tables that store pre-computed compression mappings for common data patterns. Instead of performing complex compression calculations in real-time, the system copies pre-determined compression results from these tables, significantly reducing processor requirements and energy consumption on constrained devices.
2Use of energy by moving object
If data compression techniques are implemented to reduce data size, then energy consumption is reduced, but device complexity increases
Solution Approach 1:
The patent performs preliminary analysis of the data block to determine if compression is likely to be effective before applying the full compression algorithm. This preliminary check includes assessing data patterns and estimating compression ratios, allowing the system to avoid energy-intensive compression operations when they would not yield beneficial results.
Solution Approach 2:
The patent uses temporary buffer structures and working memory that are allocated for each compression block and then discarded. These short-lived data structures minimize the need for persistent complex memory management, reducing overall device complexity while enabling effective compression processing.
3Productivity
If packet header indicates compression method used, then data transmission efficiency is improved, but packet header size increases
Solution Approach 1:
The patent extracts only the essential compression method identifier from the full compression algorithm details, placing just this critical information in the packet header. The complete compression parameters and algorithms are applied during data processing but their full descriptions are not included in the header, minimizing header overhead while maintaining transmission efficiency.
Data Source
AI summary
Techniques for data compression for efficient network management are described herein. In one example, group(s) of bytes are formed from among input bytes to be compressed. The groups are formed by including bytes having at least a certain number (e.g., three) zero-valued most significant bits (MSBs). A byte of input data having several zero-valued MSBs may be in several groups. A group having the largest product (number of bytes in the group times number of zero-valued MSBs in all bytes in the group) may be selected. A compressed-bytes array may be formed with data of the selected group of bytes, wherein the number of zero-valued MSBs originally present in all of the bytes of the group of bytes has been removed (to compress the array). An uncompressed-bytes array may be formed with bytes of the input bytes of data not in the selected group of bytes. An address-bit array may be formed to indicate the array in which data associated with each of the input bytes of data is stored.