Multi-Modal Fiber Reliability Assessment Across Multiple Time Horizons
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Solution Overview
Problem
Conventional network diagnostic tools provide limited and instantaneous views of network connection status, failing to effectively assess fiber connection reliability over various time horizons and requiring multiple resources to identify root causes of issues, which can take hours or days.
Innovation Solution
A multi-modal data approach integrating Optical Network Terminal (ONT) alarm data, Remote Authentication Dial-In User Services (RADIUS) data, and Residential Gateway (RG) outage data to provide a comprehensive view of fiber connection reliability, utilizing higher and lower-frequency data capture to determine shorter-term and longer-term connection reliability values, and predict service disruptions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional network diagnostic tools are used to monitor network connection status, then instantaneous connectivity assessment is provided, but comprehensive reliability evaluation over various time horizons cannot be achieved
Solution Approach 1:
The patent segments the network monitoring system into multiple data collection points (ONT, RADIUS, RG) operating at different frequencies. Each segment captures specific aspects of network behavior at appropriate time scales, enabling comprehensive reliability evaluation without requiring all data to be collected simultaneously at maximum frequency.
Solution Approach 2:
The patent introduces a temporal dimension by collecting data at multiple frequencies (higher frequency for short-term reliability, lower frequency for long-term reliability). This multi-frequency approach adds a time-scale dimension to traditional single-frequency monitoring, enabling holistic reliability assessment across various time horizons.
2Loss of information
If multiple data sources are integrated to assess connection reliability, then comprehensive network insights are obtained, but system complexity increases
Solution Approach 1:
The patent creates a universal data processing framework that handles multiple data types (ONT alarm data, RADIUS data, RG outage data) through a common architecture. The system uses unified data structures and processing logic that can accommodate different data sources, reducing the need for separate specialized processing pipelines for each data type.
Solution Approach 2:
The patent introduces intermediate data processing layers that act as mediators between the various data sources and the final reliability assessment. These intermediate layers normalize, validate, and correlate data from different sources before analysis, simplifying the overall system architecture by abstracting the complexity of multi-source integration.
3Measurement precision
If high-frequency data capture is used to monitor connection status, then short-term reliability is accurately determined, but longer-term reliability assessment becomes less effective
Solution Approach 1:
The patent implements dynamic data collection strategies where the system adapts its monitoring frequency based on the time horizon of interest. For short-term reliability assessment, the system uses high-frequency capture; for long-term reliability, it switches to lower-frequency capture. This dynamic adjustment optimizes the balance between measurement precision and monitoring duration.
Solution Approach 2:
The patent employs periodic data collection at varying intervals to capture different aspects of network behavior. High-frequency periodic sampling captures short-term fluctuations and immediate issues, while lower-frequency periodic sampling captures long-term trends and chronic problems. The system combines these periodic actions to achieve comprehensive reliability assessment.
Data Source
AI summary
Aspects of the subject disclosure may include, for example, receiving first data associated with users of a communication system; receiving second data associated with the users, wherein each data point of the second data has been obtained at a data capture frequency different from the data points of the first data; grouping together, for a first particular user of the plurality of users, each data point of the first data that has a first identifier corresponding to the first particular user, wherein the grouping together of each data point of the first data results in a first data set for the first particular user; grouping together, for the first particular user, each data point of the second data that has the first identifier corresponding to the first particular user, wherein the grouping together of each data point of the second data results in a second data set for the first particular user; and determining, based upon the first and second data sets, a shorter-term connection reliability value for the first particular user and a longer-term connection reliability value for the first particular user. Other embodiments are disclosed.