Self-Healing IoT Network via Virtual Payloads
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Solution Overview
Problem
The increasing complexity and number of Internet of Things (IoT) devices make human intervention to identify and resolve technical issues in IoT systems infeasible, necessitating automated methods for detecting failures and modifying operations to ensure high reliability and minimize downtime.
Innovation Solution
A self-healing and alerting mechanism is implemented in IoT systems, using fog nodes and cloud computing to dynamically generate virtual payloads, monitor communication paths, and apply rule-based responses, including exponential back-off for restart commands, to identify and rectify failures, ensuring minimal downtime and scalability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the number of IoT devices and system complexity increases, then the system can handle more functions and data, but manual verification and operations become infeasible
Solution Approach 1:
The system implements automated self-verification through virtual payloads that traverse communication paths and automatically detect failures. The system heals itself by dynamically generating repair payloads and modifying operations without human intervention, allowing the system to serve its own verification and maintenance needs.
Solution Approach 2:
The system employs continuous feedback loops where virtual payloads monitor communication paths and provide real-time status information. When failures are detected, the system automatically adjusts operations and triggers healing mechanisms, creating a closed-loop control system that adapts to changing conditions.
2Reliability
If automated detection and healing mechanisms are implemented, then system reliability improves, but device complexity increases
Solution Approach 1:
The patent introduces virtual payloads as intermediary entities that perform detection and verification functions. These lightweight virtual objects traverse communication paths and interact with system components without requiring permanent installation or complex configuration, thereby improving reliability while minimizing added complexity.
Solution Approach 2:
The system dynamically modifies operational parameters such as payload generation frequency, communication path selection, and healing trigger thresholds based on system conditions. This allows the system to adapt its complexity level and resource consumption according to actual needs, maintaining reliability while avoiding unnecessary complexity.
3Difficulty of detecting and measuring
If virtual payloads are used to monitor communication paths, then failure detection capability improves, but resource consumption increases
Solution Approach 1:
The system employs virtual payloads selectively rather than continuously monitoring all communication paths at all times. Virtual payloads are generated based on specific triggers or conditions, performing detection only when necessary. This partial action approach maintains adequate failure detection capability while significantly reducing overall resource consumption compared to continuous monitoring.
Data Source
AI summary
A method and apparatus for self-adjusting networks including internet-of-things (IoT) devices is provided. An exemplary system includes a source discovery system configured to identify if a source sending a message is in a database, and, if not, add the source to the database and rank the source by link metrics of messages received from the source. A sink discovery system is configured to identify if a sink receiving a message is in a database, and, if not, add the sink to the database. The sink discovery system is configured to rank the sink by link metrics of messages responded to by the sink. A dynamic mapping system is configured to create a dynamic map of communications between a source and a sink, and implement a self-healing subsystem to restore a loss of communications between a source and a sink.