Node Distance Measurement in Complex Networks

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Solution Overview

Problem

Existing methods fail to effectively measure the distance between nodes in complex networks, as they do not accurately reflect the dynamic and varied conditions of data transmission rates and network configurations.

Innovation Solution

The method involves forming n-dimensional spaces using randomly selected nodes, where N nodes form n-dimensional spaces with N > n, and calculating distances based on the positions of other nodes within these spaces, using coordinates determined by distances between core points and other nodes, allowing for more accurate measurement of distances in complex network configurations.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If traditional distance measurement methods are used in complex networks, then the measurement process is simple, but the measurement precision deteriorates because the methods cannot accurately reflect dynamic data transmission rates and network configurations

Engineering Contradiction:
Improvedistance measurement precisionVSAvoidmeasurement method complexity
Core Design Contradiction:
Measurement precisionVSDevice complexity

Solution Approach 1:

The patent transforms the network distance measurement problem from a one-dimensional scalar value to an n-dimensional vector space representation. By mapping nodes and distances into an n-dimensional space where n > number of dimensions, the system captures multi-dimensional characteristics of network topology and transmission dynamics, thereby improving measurement precision without requiring overly complex computational procedures

Inventive Principle:
Principle #17Another dimension (Dimensionality change)

Solution Approach 2:

The patent changes the parameter representation from traditional single-value distance metrics to n-dimensional coordinate vectors. Each node is represented by n coordinates that encode multiple network characteristics simultaneously, allowing the system to reflect dynamic transmission rates and configuration changes while maintaining a systematic and manageable measurement approach

Inventive Principle:
Principle #35Parameter changes

2Reliability

If n-dimensional spaces are formed using randomly selected nodes, then the distance measurement reflects dynamic network conditions accurately, but the computational complexity increases

Engineering Contradiction:
Improvedistance measurement reliabilityVSAvoidcomputational complexity
Core Design Contradiction:
ReliabilityVSDevice complexity

Solution Approach 1:

The patent performs preliminary actions by randomly selecting n nodes (where n > number of dimensions) to form the basis of the n-dimensional space before measuring distances between other nodes. This preliminary construction of the dimensional space framework allows subsequent distance measurements to reliably reflect dynamic network conditions while avoiding the need for complex real-time computations during the actual measurement process

Inventive Principle:
Principle #10Preliminary action

Solution Approach 2:

The patent uses excessive action by selecting more nodes (n nodes) than the minimum required to span the dimensional space (number of dimensions). This ensures that the n-dimensional space can accurately capture the complexity of network configurations and transmission dynamics, improving reliability while the computational burden remains manageable due to the systematic approach

Inventive Principle:
Principle #16Partial or excessive action

Data Source

PatentEP2555009B1Method and apparatus for measuring the distance between nodes
Publication Date: 2019.10.23 CDNETWORKS CO LTD
  • EP2555009B1 patent drawingFigure 1~2
  • EP2555009B1 patent drawingFigure 3
  • EP2555009B1 patent drawingFigure 4

AI summary

Disclosed are a method and an apparatus for measuring distances between nodes. According to an exemplary embodiment of the present invention, N or more nodes among a plurality of nodes located in a network are randomly selected, n-dimensions (where N>n and n≥1) are formed by using the randomly selected N or more nodes, coordinates of other nodes are determined in the formed n-dimensional spaces by using distances between the randomly selected N or more nodes and other nodes, and distances between the plurality of nodes located in the network are calculated by using the determined coordinates. According to the present invention, the distance between nodes located in a network may be more effectively measured.