Behavior Deviation Model for Network Node Selection
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Solution Overview
Problem
Conventional network routing protocols lack control over data forwarding paths, making it difficult to manage and secure complex networks, where path perception and source routing are essential for optimizing data transmission.
Innovation Solution
A method and apparatus for selecting a recommended node based on a behavior deviation model, which determines candidate paths, calculates behavior deviations, and identifies a node with the smallest average deviation as a recommended node to ensure secure and efficient communication.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional routing protocols are used to find optimal paths based on metric indicators, then forwarding efficiency is improved, but path controllability deteriorates
Solution Approach 1:
The patent introduces a behavior deviation model as an intermediary mechanism between the routing protocol and path selection. This model evaluates nodes along candidate paths and selects recommended nodes based on behavior deviations, enabling path controllability while maintaining forwarding efficiency through automated node selection.
Solution Approach 2:
The patent implements feedback by calculating behavior deviations for nodes and using these deviations to select recommended nodes for path construction. The system continuously monitors node behavior and adjusts path selection based on feedback from behavior deviation calculations, achieving controllable forwarding paths.
2Reliability
If behavior deviation calculation is performed for all candidate nodes to ensure security, then path security is improved, but calculation complexity increases
Solution Approach 1:
The patent applies local quality by calculating behavior deviations selectively for recommended nodes rather than all candidate nodes. The system identifies key nodes along candidate paths and performs behavior deviation calculations only for these nodes, reducing overall calculation complexity while maintaining path security through focused evaluation of critical nodes.
Solution Approach 2:
The patent uses partial action by performing behavior deviation calculations for a subset of nodes (recommended nodes) rather than all candidate nodes. This selective approach reduces calculation complexity while still ensuring path security through evaluation of behavior deviations for nodes that most impact path reliability.
3Manufacturing precision
If multiple candidate paths are evaluated to find the optimal path, then path optimization is improved, but evaluation time increases
Solution Approach 1:
The patent applies preliminary action by pre-calculating behavior deviations for nodes before final path selection. This allows the system to quickly evaluate multiple candidate paths using pre-computed behavior deviation data, reducing evaluation time while maintaining path optimization through comprehensive multi-path assessment.
Data Source
AI summary
A method for selecting a recommended node in a behavior deviation model includes: determining a candidate path starting from a delegation node to a target node based on a preset network topology; determining candidate recommended nodes passing through each candidate path, and acquiring a first behavior deviation corresponding to the target node at each candidate node; reading a second behavior deviation of each candidate recommended node from a central node in the network topology; calculating an average deviation value for the target node based on second behavior deviations and first behavior deviations; determining a candidate path with the smallest average deviation value as a target candidate path; and in response to the average deviation value of the target candidate path being less than or equal to a preset warning value, determining the candidate recommended node on the target candidate path as a recommended node.