A big data-based information system service method

By constructing a directed acyclic graph, masking physical arrival timestamps, calculating uncertainty indexes, and skipping database lock decision instructions, the system response performance avalanche problem caused by traditional discrete state machine logic in high-concurrency out-of-order data stream processing of big data information systems is solved, thereby improving the stability and accuracy of the system.

CN122432218APending Publication Date: 2026-07-21SHENZHEN YUNHENG NETWORK TECHNOLOGY CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
SHENZHEN YUNHENG NETWORK TECHNOLOGY CO LTD
Filing Date
2026-04-23
Publication Date
2026-07-21

AI Technical Summary

Technical Problem

When processing high-concurrency out-of-order data streams, existing big data information systems suffer from a significant drop in system response performance due to the large amount of invalid idle time in the underlying memory bandwidth and clock cycles caused by traditional discrete state machine logic and database transaction locking mechanisms.

Method used

By constructing a directed acyclic graph, masking the physical arrival timestamp, building an adjacency matrix in the memory buffer based on the business state preceding pointer, performing feature space projection operation, calculating the uncertainty index, compiling the difference increment matrix in the memory buffer ring, skipping the database lock determination instruction, directly performing matrix addition operation, and generating the system state matrix.

Benefits of technology

It reduces the probability of logical errors caused by network jitter, improves the speed of central processing unit correlation extraction, suppresses state machine logic drift and timing inversion, reduces system response latency and computing power idle queuing, and improves system stability and accuracy.

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Abstract

The application relates to the technical field of big data and discloses an information system service method based on big data. The method extracts a business state pre-pointer and a physical timestamp of a data stream, shields the timestamp to construct a directed acyclic graph when time sequence is dislocated, and compiles the directed acyclic graph into an adjacency matrix of a continuous memory interval; performs feature space projection on the matrix and a real-time data vector, calculates an uncertainty index based on a projection disturbance amount; writes data increments meeting a threshold value into a buffer ring to generate a difference increment matrix; and when responding to a query, performs element-by-element addition of the same type of matrix on a benchmark matrix and the difference increment matrix and outputs a state matrix. The application converts lock queuing and waiting into memory space operation and overcomes performance avalanche caused by high concurrency and disorder.
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