Swarm-Based Self-Healing for Network Fault Detection

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Solution Overview

Problem

Existing network healing systems lack the ability to automatically and efficiently heal faulty nodes using majority logic, relying on predefined factors or server-based approaches that do not account for dynamic adjustments based on collective decisions from healthy nodes.

Innovation Solution

A self-healing system that forms a swarm of electronic devices in a network, computes fitness values, identifies faulty nodes using majority logic, and applies healing profiles to correct issues autonomously, utilizing machine learning techniques for dynamic profile updates.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If each node heals itself using predefined rules or server-based approaches, then the system can maintain basic self-healing capability, but it cannot dynamically adapt to new fault patterns or learn from collective node experiences

Engineering Contradiction:

Improvedynamic adaptation to fault patternsVSAvoidhealing system architecture

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The patent implements feedback mechanisms where nodes continuously monitor their own health status and share fault information with the network. Healthy nodes provide feedback to faulty nodes about their operational state, enabling dynamic adaptation. The system learns from collective experiences through shared fault databases and updates healing strategies based on accumulated network-wide information.

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

Each node is equipped with self-diagnosis and self-healing capabilities through embedded agents that can independently identify faults and apply corrective actions. Nodes serve themselves by monitoring their own health metrics, comparing them against learned patterns, and executing healing procedures without external intervention, while still benefiting from collective network intelligence.

Inventive Principle:

Principle #25Self-service

2Measurement precision

If manual intervention is used to diagnose and repair faulty nodes, then accurate problem identification can be achieved, but the process becomes time-consuming and error-prone

Engineering Contradiction:

Improvefault detection accuracyVSAvoidhealing time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The patent replaces manual mechanical inspection and diagnosis with automated electronic monitoring systems. Nodes use software agents and algorithms to continuously assess their health status, replacing human technicians' visual and physical inspections. This substitution enables rapid, precise fault detection through automated data collection and analysis, eliminating human error and significantly reducing diagnosis time.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system introduces intelligent agents as intermediaries between the physical node components and the healing process. These agents continuously monitor node health metrics, interpret data patterns, and coordinate healing actions, serving as automated mediators that bridge the gap between fault occurrence and corrective action without requiring human intervention.

Inventive Principle:

Principle #24Intermediary (Mediator)

3Ease of operation

If predefined healing profiles are used for fault resolution, then the healing process can be standardized, but the system cannot handle novel or evolving fault conditions

Engineering Contradiction:

Improvehealing process standardizationVSAvoidhandling novel fault conditions

Core Design Contradiction:

Ease of operationVSAdaptability or versatility

Solution Approach 1:

The patent transforms static predefined healing profiles into dynamic, adaptive healing strategies. The system continuously updates healing profiles based on learned patterns from network-wide fault data and successful remediation experiences. Healing parameters and procedures evolve over time, adapting to new fault patterns while maintaining the structured approach of standardized profiles for common issues.

Inventive Principle:

Principle #15Dynamics

Data Source

PatentUS11888682B2Automated system for healing faulty node in a network and method thereof

Publication Date: 2024.01.30 SAMSUNG ELECTRONICS CO LTD

AI summary

A self-healing system for healing electronic devices in a network is provided. The system includes a memory configured to store pre-defined rules and a processor which is operatively connected to the memory configured to form a swarm the electronic devices connected in the network, store first data and second data which are related to the electronic devices on the formed swarm in a database of the swarm, compute third data of the electronic devices on the formed swarm based on the first data, compare the third data with the first data related to the electronic devices, identify a faulty of the electronic devices on the swarm based on the compared results, and correct the faulty of the electronic devices which are identified by applying the second data.