AMI Network Failure Detection via Hierarchical Graph Segmentation
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Solution Overview
Problem
Current methods for detecting communication failures in Advanced Metering Infrastructure (AMI) devices are inefficient, requiring significant communication overhead and being unable to monitor in real-time, especially in large networks, with separate techniques for IP and non-IP devices, making them impractical for widespread use.
Innovation Solution
A computer-implemented method and system that generates a graphical representation of AMI devices, computes properties based on real-time data, and modifies the representation using predefined rules to identify communication failures, prioritizing and categorizing nodes by hierarchy and criticality for optimized monitoring and detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If sequential mass pinging is performed to detect communication failures, then detection capability is improved, but communication overhead and time consumption increase significantly
Solution Approach 1:
The patent segments the AMI network into hierarchical levels (core network, distribution network, metering network) and detects communication failures at each level separately. This segmentation allows targeted monitoring of specific network segments rather than pinging all devices sequentially, reducing overall detection time while maintaining comprehensive coverage.
Solution Approach 2:
The patent implements preliminary actions by continuously monitoring network connectivity and maintaining updated network topology information. Communication failure detection is performed proactively based on pre-established network paths and device relationships, enabling early detection before complete outages occur.
2Reliability
If sequential mass pinging is performed to detect communication failures, then detection capability is improved, but network bandwidth consumption increases
Solution Approach 1:
By dividing the network into hierarchical levels and detecting failures at each level independently, the patent reduces the total number of ping operations required. Only necessary ping operations are executed based on actual network state and failure detection needs, minimizing bandwidth consumption while maintaining detection effectiveness.
Solution Approach 2:
The patent applies partial action by performing ping operations only on selected network paths and devices where communication failures are suspected or where monitoring is critical. Not all devices are pinged simultaneously, but rather a representative sample is monitored to infer overall network health, reducing bandwidth usage.
3Measurement precision
If separate detection techniques are used for IP and non-IP devices, then detection accuracy is improved, but system complexity increases
Solution Approach 1:
The patent creates a universal detection framework that handles both IP-based devices (access points, relays) and non-IP devices (smart meters) through a single integrated architecture. The same hierarchical detection model and ping-based methodology are applied across device types, with appropriate protocol adaptations, simplifying the overall system while maintaining detection accuracy for diverse devices.
4Reliability
If conventional monitoring methods are used in large networks, then comprehensive monitoring is achieved, but feasibility decreases
Solution Approach 1:
The patent makes large network monitoring feasible by segmenting the network into manageable hierarchical levels. Each level can be monitored and detected independently, allowing the system to handle large-scale networks without overwhelming computational or communication resources. This segmentation transforms an infeasible monolithic monitoring approach into a scalable hierarchical system.
Solution Approach 2:
The patent performs preliminary actions by pre-establishing network topology information, device relationships, and monitoring paths during network setup. This preliminary configuration enables efficient failure detection during operation without requiring comprehensive real-time monitoring of all device states, making large network monitoring feasible.
Data Source
AI summary
A method for optimized monitoring and identification of AMI device communication failures in an AMI network is provided. A graphical representation of AMI devices is generated comprising nodes corresponding to AMI devices and links representing connectivity between AMI devices. The graphical representation is generated based on data associated with AMI devices retrieved via AMI network in real time. Further, properties of the AMI devices are computed using the graphical representation based on values associated with the nodes corresponding to the AMI devices. The graphical representation is modified based on the computed properties and predefined rules. Nodes in the modified graphical representation are selected and processed in an order based on AMI device hierarchy, priority and criticality. Further, the graphical representation is modified based on processing of selected nodes. AMI device with communication failures are identified from at least one of the generated and modified graphical representation of AMI devices.