Data Packet Byte Segmentation for Server Stability
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Solution Overview
Problem
The analysis of large amounts of data in industrial production is cumbersome and puts significant pressure on servers, necessitating a streamlined and optimized approach to improve server stability and efficiency.
Innovation Solution
A data analyzing system comprising a pre-processing module, a converting module, a data splitting module, and a comparing module, which processes data packets by removing headers and tails, converting signal values, splitting integer values into high, middle, and low bytes, and comparing these bytes to identify abnormal data, thereby simplifying the analysis process and improving efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If data analysis is performed on large amounts of industrial production data, then comprehensive data analysis capability is achieved, but server pressure increases and service stability deteriorates
Solution Approach 1:
The patent segments data packets into high bytes, middle bytes, and low bytes for parallel processing. This segmentation enables the system to analyze large amounts of data efficiently by dividing the analysis task into smaller, manageable units that can be processed simultaneously, thereby improving productivity while maintaining service stability through reduced server pressure
Solution Approach 2:
The patent extracts and removes packet headers and tails before processing the core data. This extraction approach eliminates unnecessary data elements, reducing the overall data volume that requires intensive processing on the server, thus improving both analysis efficiency and service stability
2Measurement precision
If comprehensive data analysis is performed, then data analysis thoroughness is improved, but processing time increases
Solution Approach 1:
The patent performs preliminary actions by removing packet headers and tails before the main analysis process. It also pre-segments the data into high, middle, and low bytes. These preliminary actions reduce the data volume and prepare the data structure for faster processing, thereby maintaining thoroughness while reducing processing time
Solution Approach 2:
By segmenting data into high bytes, middle bytes, and low bytes, the patent enables parallel processing of different byte segments. This segmentation allows comprehensive analysis of all data components while reducing overall processing time through concurrent execution of analysis operations on each segment
3Measurement precision
If detailed data comparison is performed to identify abnormal data, then detection accuracy is improved, but computational complexity increases
Solution Approach 1:
The patent segments data into high bytes, middle bytes, and low bytes, and compares corresponding byte segments in parallel. This segmentation approach maintains high detection accuracy by examining each byte level in detail while reducing computational complexity through parallel processing of segmented data, avoiding the need for complex full-data comparisons
Data Source
AI summary
A method and system for accelerating analysis of large-scale data that reads a data packet from a queue, and after performing data processing on the data packet, a first high, middle, and low byte of the processed data packet is cyclically read; a preset signal reference value is read, and the preset signal reference value is converted into a collected value according to a preset signal transformation ratio and a correction factor; the collected value is converted into an integer value, and the integer value is split into a second high, middle, and low byte; and the first high, middle, and low byte of the processed data packet is compared with the second high, middle and low byte of the integer value in a preset way. A determination as to whether the data of the packet is abnormal or not is made based on the result of the comparison.