Return and Replacement Protocol for Network Device Fault Management
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Solution Overview
Problem
Network devices often fault and become unresponsive, leading to diagnostic information loss and increased costs for troubleshooting, as existing methods struggle to manage faulting devices effectively, especially when they crash or enter endless reboot loops, disrupting network services and requiring manual Return Merchandise Authorization (RMA) processes.
Innovation Solution
The implementation of the Return and Replacement Protocol (RRP) allows network devices to propagate crash and error data to neighboring devices, enabling continuous diagnostic data collection and analysis, even when a device is unresponsive, using lightweight daemons to monitor health states and broadcast critical events, and employing machine learning models to predict when a device needs replacement, minimizing service disruptions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If a network device faults and becomes unresponsive, then diagnostic information is lost, but manual troubleshooting and RMA processes increase time and expense
Solution Approach 1:
The system performs preliminary actions by continuously collecting and storing diagnostic information in a buffer memory before the device actually faults. The lightweight daemon monitors system events and prepares diagnostic data in advance, so when a fault occurs, the information is already available for immediate analysis without requiring manual troubleshooting time.
Solution Approach 2:
The patent introduces an intermediary component - a lightweight daemon process that acts as a mediator between the network device and external troubleshooting systems. This daemon continuously monitors system events, collects diagnostic information, and maintains a buffer of crash data, serving as an intermediary that preserves information even when the device becomes unresponsive.
2Productivity
If diagnostic information is collected continuously, then troubleshooting efficiency improves, but device complexity increases
Solution Approach 1:
The system implements self-service by incorporating a lightweight daemon within the network device itself that autonomously monitors system events, collects diagnostic information, and maintains crash data buffers without requiring external intervention. This self-serving mechanism improves troubleshooting efficiency while minimizing the need for additional complex external systems.
Solution Approach 2:
The patent employs a lightweight daemon - a simple, low-overhead software component that serves the purpose of continuous monitoring without adding significant complexity. The crash data buffer acts as a disposable storage mechanism that holds diagnostic information temporarily until needed, then can be cleared or replaced, avoiding the need for permanent complex storage systems.
3Reliability
If manual RMA processes are used for faulting devices, then device replacement occurs, but service disruption and costs increase
Solution Approach 1:
The system implements feedback mechanisms where the lightweight daemon continuously monitors device health and automatically triggers RMA processes when specific fault conditions are detected. This feedback loop eliminates manual intervention, maintains network service continuity by automating the replacement workflow, and preserves diagnostic information for manufacturing improvement.
Solution Approach 2:
The patent enables the network device to self-manage the RMA process through the lightweight daemon, which automatically detects faults, prepares diagnostic information, and initiates replacement procedures without requiring manual operator intervention. This self-service approach maintains service reliability while simplifying the overall RMA process.
Data Source
AI summary
Systems and methods provide for managing faulting network devices. A first network device can receive an error. The first network device can generate one or more frames including data indicative of the error. The first network device can broadcast the one or more frames to one or more neighboring network devices. It may be determined that the first network device is inaccessible. The first data can be retrieved and presented from a second network device among the one or more neighboring network devices. In some embodiments, a network management system can utilize the first data to generate a machine learning model that classifies whether network devices are instances of network devices designated for a Return Merchandise Authorization (RMA) process. In some embodiments, the network management system can apply the first data to a machine learning classifier to determine whether to initiate the RMA process for the first network device.