Autonomous Codes for Data Packet Correlation and Processing
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Solution Overview
Problem
In high-speed, real-time, and large data volume scenarios, existing data processing systems face inefficiencies due to complex timing logic and interlocking events caused by the correlation between data packets, making it challenging to design an effective task management process, especially in multi-node computing clusters.
Innovation Solution
The implementation of a data processing mechanism using autonomous codes within data packets, which combines data and program information to eliminate timing complexities, allowing for optimized task allocation and reduced errors, thereby enhancing efficiency and reliability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data packets are processed according to complex timing logic to handle correlation between packets, then processing accuracy is improved, but system efficiency deteriorates
Solution Approach 1:
Each data packet carries its own tags and correlation information, enabling self-identification and self-grouping. The system does not need complex external coordination to determine which packets are correlated; the packets themselves contain the information needed to be processed correctly together, thus maintaining accuracy while improving efficiency.
Solution Approach 2:
Tags and correlation information are attached to data packets before they enter the processing system. This preliminary action ensures that when packets arrive, their relationships are already established and identifiable, eliminating the need for complex runtime timing logic and coordination overhead.
2Adaptability or versatility
If message-based communication mechanism is used between task management process and computing nodes, then coordination capability is improved, but system complexity deteriorates
Solution Approach 1:
The patent merges data, tags, and processing instructions into a single integrated data packet structure. This combination eliminates the need for separate message-based communication between task management and computing nodes, as all necessary information is embedded within the packet itself, reducing system complexity while maintaining coordination capability.
Solution Approach 2:
The data packet structure serves multiple functions simultaneously: it carries data, contains correlation tags, specifies processing requirements, and enables self-routing. This multi-functionality replaces multiple separate communication mechanisms, simplifying the system architecture.
3Productivity
If task management process optimizes allocation of computing nodes and tasks, then resource utilization is improved, but timing coordination complexity deteriorates
Solution Approach 1:
Data packets with embedded tags can be independently routed and allocated to computing nodes without complex timing coordination. The tags enable automatic identification of correlated packets, allowing task management to optimize resource allocation simply by grouping packets with matching tags, rather than managing complex timing relationships.
Data Source
AI summary
Methods and apparatuses are provided for data processing. The method includes receiving a first data packet and a second data packet; associating first codes with the first data packet and second codes with the second data packet to generate a combined data packet after receiving the first data packet and the second data packet, wherein the first codes and the second codes specify processing to be performed to the a combined data packet; generating the combined data packet comprising the first data packet and the second data packet in response to determining that the first data packet and the second data packet are correlated; and performing the processing to the combined data packet in accordance with the first codes or the second codes.