Networking System Node Abnormality Detection via Current Monitoring
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Solution Overview
Problem
Existing networking systems lack the ability to detect and isolate abnormal nodes, such as those experiencing failures or external attacks, which can disrupt communication and prevent the network from maintaining functionality.
Innovation Solution
A networking system with nodes equipped with data-driven processors, consumption current detection units, and abnormality discrimination units that monitor and isolate abnormal nodes by analyzing cumulative consumption current values, allowing for the detection and isolation of faulty nodes without dedicated life-and-death monitoring configurations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If nodes are connected via ad hoc network without dedicated monitoring configuration, then device complexity is reduced, but ability to detect abnormal nodes deteriorates
Solution Approach 1:
Each node in the network monitors its own consumption current and uses this information to detect abnormalities in other nodes. The system leverages the inherent correlation between processing load and current consumption without requiring external monitoring infrastructure, allowing nodes to self-diagnose and report their status to neighboring nodes.
Solution Approach 2:
The consumption current detection mechanism serves dual purposes: it monitors the processing load of the local node while simultaneously enabling abnormality detection of other nodes in the network. This multi-functional approach eliminates the need for separate monitoring systems, reducing overall device complexity while maintaining reliable abnormality detection.
2Device complexity
If consumption current monitoring is implemented without dedicated life-and-death monitoring configuration, then device complexity is reduced, but measurement precision of abnormality detection may deteriorate
Solution Approach 1:
The system monitors consumption current as a proxy parameter for processing load and node health status. By establishing threshold values and ranges for normal current consumption, the system can accurately detect abnormalities when current values deviate from expected ranges, maintaining detection precision without requiring direct monitoring of node life status.
Solution Approach 2:
Consumption current acts as an intermediary parameter that indirectly reflects the health status and processing load of nodes. Instead of directly monitoring complex node states, the system uses current consumption as a measurable intermediary that correlates with node functionality, enabling accurate abnormality detection through a simple, indirect measurement approach.
3Productivity
If nodes process data from abnormal nodes, then network connectivity is maintained, but network stability deteriorates due to propagation of harmful effects
Solution Approach 1:
Each node provides feedback to neighboring nodes about its abnormality status based on consumption current monitoring. When a node detects that another node is abnormal, it feeds back this information and adjusts its behavior accordingly, such as discarding data from abnormal nodes. This feedback mechanism allows the network to maintain connectivity with healthy nodes while isolating abnormal nodes to prevent propagation of harmful effects.
Solution Approach 2:
The network dynamically segments itself by identifying and isolating abnormal nodes through consumption current monitoring. Healthy nodes continue to communicate and process data, while abnormal nodes are effectively segmented out from the active communication paths. This segmentation maintains overall network productivity through the healthy portion while preventing stability degradation from spreading across the entire network.
Data Source
AI summary
In a networking system including a plurality of nodes connected with each other by a communication network, each node includes an abnormality discrimination unit configured, when a cumulative consumption current at the time of processing the data received from other node is out of a range (of current values estimated in advance based on an event at the other node, to discriminate the other node as an abnormal. By the networking system, the abnormality of the nodes on the network may be detected with a simple configuration.