Network Node Outage Prediction via Characteristic Analysis
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Solution Overview
Problem
Current systems lack real-time monitoring and predictive capabilities to prevent network outages, leading to potential downtime despite the presence of complementary nodes that can maintain system operation.
Innovation Solution
A system for monitoring network processing using node analysis, which includes processing devices that receive node operation information, determine node characteristics, compare them to expected values, and generate a cluster node operation plan to ensure minimum system uptime by identifying potential outages and adjusting node availability accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If real-time monitoring and predictive capabilities are implemented, then network outage prevention is improved, but system complexity increases
Solution Approach 1:
The system performs preliminary analysis of node operation information against historical patterns to predict potential outages before they occur. By proactively identifying nodes at risk based on characteristic comparisons with expected values, the system enables preventive maintenance actions that avoid actual outages, thus improving reliability without requiring complex real-time intervention mechanisms.
Solution Approach 2:
The system automatically monitors node operation information, compares characteristics against expected values, and generates outage predictions without requiring external intervention. The automated comparison process and self-adjusting monitoring capabilities reduce the need for complex manual management systems while maintaining high reliability through continuous autonomous assessment.
2Measurement precision
If node operation information is continuously monitored and analyzed, then outage prediction accuracy is improved, but data processing requirements increase
Solution Approach 1:
The system extracts only the most relevant node operation characteristics for comparison against expected values, rather than processing all available data. By selectively identifying and analyzing key performance indicators that correlate with outage patterns, the system achieves high prediction accuracy while minimizing the computational resources and energy required for data processing.
3Productivity
If cluster node operation plans are dynamically adjusted, then system availability is maintained, but operational complexity increases
Solution Approach 1:
The system pre-determines cluster node operation plans based on predicted outages, identifying which nodes should be maintained or replaced before actual failures occur. By planning maintenance activities in advance based on predictive analytics, the system maintains continuous availability through pre-coordinated node operations without requiring complex real-time reconfiguration during outages.
Data Source
AI summary
Systems, methods, and computer program products are provided for monitoring network processing using node analysis. The method includes receiving node operation information relating to a node command from one or more nodes. The one or more nodes are grouped into a cluster. The method also includes determining one or more node characteristics based on the node operation information. The method further includes comparing the node characteristic(s) of the node command to expected node characteristic(s). The method still further includes determining a node outage likelihood. The node outage likelihood indicates the likelihood the given node will experience a node outage. The method also includes determining a cluster node operation plan. The cluster node operation plan is configured to determine the nodes of the cluster that must be in operation in an event of the node outage of the given node.