Network Traffic Tracing for Dynamic Business Process Modeling

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Solution Overview

Problem

Current methods for assessing business processes are manual, time-consuming, and produce static assessments, which are unreliable and costly, failing to discover unknown business processes executing within a network fabric in real-time.

Innovation Solution

A system that generates an information model of business processes by recursively tracing data packets in a network, using a node identifier as a seed to identify and analyze data packets, and applying machine learning algorithms to create a dynamic model of business processes, enabling real-time analysis and identification of inefficiencies.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If manual methods are used to assess business processes, then detailed analysis can be performed, but the process becomes time-consuming and costly

Engineering Contradiction:
Improvebusiness process assessment accuracyVSAvoidassessment time
Core Design Contradiction:
Measurement precisionVSLoss of time

Solution Approach 1:

The patent replaces manual mechanical assessment methods with automated electronic systems that capture, trace, and analyze network traffic data. The system automatically generates business process models by tracing data packets through the network fabric, eliminating the need for manual observation and documentation while maintaining high measurement precision through systematic data collection and analysis.

Inventive Principle:
Principle #28Mechanics substitution (Replace mechanical system)

2Adaptability or versatility

If manual assessment methods are used, then existing business processes can be analyzed, but unknown business processes cannot be discovered

Engineering Contradiction:
Improvebusiness process discovery capabilityVSAvoidassessment reliability
Core Design Contradiction:
Adaptability or versatilityVSReliability

Solution Approach 1:

The system enables self-service by automatically discovering and modeling business processes through network traffic analysis without requiring manual intervention. The electronic code recursively traces data packets and autonomously generates business process models, allowing the system to identify both known and unknown processes reliably through objective data-driven analysis rather than subjective manual assessment.

Inventive Principle:
Principle #25Self-service

3Productivity

If static assessments are produced, then the assessment process is simpler, but the results become outdated quickly

Engineering Contradiction:
Improveassessment update speedVSAvoidmodeling system complexity
Core Design Contradiction:
ProductivityVSDevice complexity

Solution Approach 1:

The patent implements continuous useful action by continuously capturing and analyzing network traffic to maintain up-to-date business process models. The system operates continuously to trace data packets and regenerate models as needed, ensuring that business process information remains current without requiring periodic manual reassessments, thus achieving high productivity despite increased system complexity.

Inventive Principle:
Principle #20Continuity of useful action

Data Source

PatentUS10248923B2Business process modeling based on network traffic
Publication Date: 2019.04.02 CISCO TECHNOLOGY INC
  • US10248923B2 patent drawing
  • US10248923B2 patent drawing
  • US10248923B2 patent drawing

AI summary

The present disclosure describes approaches for generating an information model of a business process. One example is a method comprising receiving an input of an identifier, wherein the identifier corresponds to a node in a network; recursively tracing data packets in the network, wherein the identifier is utilized as a seed for the tracing; and generating an information model of the business process based on the data packets. In further examples, the recursively tracing data packets in the network comprises: identifying, based on the identifier, data packets transferred between the node and one or more nodes; retrieving, from the data packets, one or more identifiers corresponding to the one or more nodes; and identifying, based on the one or more identifiers, additional data packets transferred between the one or more nodes and one or more additional nodes.