Integrated IoT Clustering With Automatic K3s Installation
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Solution Overview
Problem
Existing IoT devices with limited resources face high system requirements and manual configuration challenges when using Rancher K3s program for clustering, necessitating a technology for automatic installation and clustering.
Innovation Solution
An integrated clustering system with a master node, worker nodes, and a system control unit that sets environment variables, generates access tokens, and manages runtime comparisons to automatically cluster IoT devices using Rancher K3s program.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If Rancher K3s program is used to cluster IoT devices, then clustering capability is achieved, but manual configuration and installation complexity increases
Solution Approach 1:
The system enables self-service automation where the master node automatically generates environment variables, access tokens, and configuration files that are transmitted to worker nodes. The system performs self-configuration and self-installation without requiring manual user intervention, resolving the contradiction between achieving clustering capability and reducing configuration complexity.
Solution Approach 2:
The master node performs preliminary actions by pre-generating all necessary configuration data including environment variables, access tokens, and installation scripts before the clustering process begins. These pre-prepared configurations are then automatically distributed to worker nodes, eliminating the need for manual configuration during the clustering process.
2Productivity
If Kubernets is used to manage IoT applications, then effective management and orchestration is achieved, but system requirements become too high for limited IoT resources
Solution Approach 1:
The patent adopts Rancher K3s, a lightweight, optimized version of Kubernetes specifically designed for resource-constrained environments like IoT devices. This alternative provides essential container orchestration capabilities with significantly reduced system requirements, making it suitable for IoT devices with limited resources while maintaining effective application management and orchestration.
3Ease of manufacture
If manual configuration is required for K3s program installation, then installation control is maintained, but user convenience and automation level decrease
Solution Approach 1:
The system implements self-service automation where the master node automatically generates environment variables, access tokens, and configuration files that are transmitted to worker nodes. The system performs self-configuration and self-installation without requiring manual user intervention, resolving the contradiction between achieving clustering capability and reducing configuration complexity.
Solution Approach 2:
The master node acts as an intermediary that automatically generates and distributes all necessary configuration data to worker nodes. This intermediary mechanism eliminates the need for manual configuration by serving as an automated bridge between the clustering initiation and the actual node configuration, thereby improving installation ease while maintaining high automation levels.
Data Source
AI summary
Disclosed is an integrated clustering system including a master node that sets environment setting for clustering and generate an access token by installing a management program, a plurality of worker nodes that set environment setting based on an environment variable including an IP address of the master node and the access token and perform clustering with the master node by installing the management program, and a system control unit that extracts runtimes of clustering groups including the master node and the plurality of worker nodes which are clustered, and compares the runtime of one of the clustering groups with the runtimes of other clustering group than the one clustering group.