Network Node Data Processing Mode Switching
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Solution Overview
Problem
Network nodes face inefficiencies in processing data due to the need for either stateful or stateless modes, leading to resource-intensive processing and potential service degradation, especially in high traffic environments, without the ability to dynamically switch between these modes based on specific criteria.
Innovation Solution
A system and method that allow network nodes to switch between stateful and stateless data processing modes based on manual configurations and dynamic criteria, such as network conditions and resource availability, by analyzing packet information and applying policy sets to determine whether to maintain or discard state information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If stateful processing is used to monitor and track packet conversations for security and correlation, then processing accuracy and reliability are improved, but resource consumption and device complexity increase significantly
Solution Approach 1:
The patent segments data flows into micro-flows and groups them into macro-flows, allowing stateful processing to be applied selectively at different levels. This segmentation enables the system to track only essential conversation patterns without maintaining state for every individual packet, thereby improving reliability while reducing device complexity.
Solution Approach 2:
The patent implements dynamic switching between stateful and stateless processing modes based on traffic characteristics and network conditions. The system can transition from maintaining full packet state to using simplified flow state representations, allowing processing accuracy to be maintained when needed while reducing complexity under normal conditions.
2Reliability
If stateful processing is used to maintain packet history and correlate conversations, then service reliability is improved, but processing speed and productivity deteriorate in high traffic environments
Solution Approach 1:
By dividing data flows into micro-flows and organizing them into macro-flows, the patent enables parallel processing of multiple flow groups. This segmentation allows the system to maintain conversation correlation for reliability while processing multiple flows simultaneously, thereby improving processing speed in high traffic environments.
Solution Approach 2:
The patent applies stateful processing partially by maintaining state information only for macro-flows rather than every individual packet. This partial state maintenance provides sufficient service reliability for conversation correlation while significantly reducing processing overhead and improving throughput.
3Productivity
If stateless processing is used to reduce resource usage and improve scalability, then productivity and ease of operation are improved, but ability to maintain conversation state and reliability deteriorates
Solution Approach 1:
The patent segments traffic into micro-flows and macro-flows, enabling stateless processing at the packet level while maintaining aggregated flow state. This segmentation allows high processing efficiency for individual packets while preserving conversation correlation at the macro-flow level, thus maintaining reliability.
Solution Approach 2:
The patent transitions from maintaining state in the packet dimension to maintaining state in the flow aggregation dimension. By moving state maintenance to the macro-flow level rather than the individual packet level, the system achieves both high processing efficiency and reliable conversation correlation.
4Measurement precision
If stateful processing is used to correlate multi-channel applications, then service accuracy is improved, but resource consumption and loss of energy increase
Solution Approach 1:
The patent segments multi-channel applications into distinct macro-flows, allowing stateful processing to be applied to flow groups rather than individual packets across all channels. This segmentation maintains service accuracy for correlating applications while significantly reducing resource consumption by processing at the aggregated flow level.
Data Source
AI summary
The present invention provides systems and methods enabling network nodes to process data in a more efficient manner. In one aspect, the present invention analyzes data processed in a network node and determines whether the data requires processing in a stateful mode. If the data does not require processing in a stateful mode, the present invention processes the data in a stateless mode thereby saving processing resources. Embodiments of the present invention permit selection of processing modes in both manual and dynamic manners. Further, the determination of whether to process data in a stateful or a stateless mode may be made in response to various stimuli.