Cloud Outage Stream Management for Cable Networks
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current systems for managing cable network outages are inefficient due to the generation of numerous non-actionable service tickets, leading to inefficient use of resources and delayed responses to actionable issues.
Innovation Solution
A cloud-based outage stream management component utilizing serverless computing and machine learning to analyze cable system performance data, differentiate between actionable and non-actionable events, and optimize the generation of service tickets, thereby reducing unnecessary resource allocation and improving response times.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional service ticket systems are used to monitor cable network outages, then all service performance issues are captured, but numerous non-actionable tickets are generated causing resource inefficiency
Solution Approach 1:
The patent introduces an intermediary machine learning model that sits between the traditional service ticket system and the response team. This model analyzes service performance data and determines whether detected outages are actionable or non-actionable, filtering out false positives before they reach human technicians. The intermediary layer maintains reliable outage detection while preventing resource waste on non-actionable tickets.
Solution Approach 2:
The system implements self-service by enabling the outage detection system to automatically classify and filter tickets using machine learning algorithms. The model learns from historical data to independently distinguish between actionable and non-actionable outages, reducing the need for manual review and improving resource allocation without sacrificing detection accuracy.
2Productivity
If machine learning models are deployed to differentiate actionable and non-actionable events, then resource efficiency improves, but system complexity increases
Solution Approach 1:
The patent segments the outage management system into distinct functional components: data collection, machine learning model processing, ticket generation, and response coordination. By dividing the system into modular segments, the complexity is managed through clear separation of concerns, making the system easier to deploy, maintain, and scale while achieving improved resource efficiency.
3Reliability
If service tickets are generated for all detected outages, then comprehensive monitoring is achieved, but response time to actionable issues is delayed due to manual review
Solution Approach 1:
The patent applies preliminary action by pre-classifying service tickets as actionable or non-actionable using machine learning models before human technicians review them. This advance classification filters out non-actionable tickets in advance, so when technicians receive tickets, they are already prioritized and validated, significantly reducing response time while maintaining comprehensive monitoring coverage.
Data Source
AI summary
This disclosure describes systems, methods, and devices related to network outage management. A method may include receiving, by a cloud-based system, a first indication of a first cable system outage; instantiating, by the cloud-based system, a first computing instance associated with generating event data indicative of the first cable system outage; instantiating, by the cloud-based system, a second computing instance associated with a machine learning model; generating, by the cloud-based system, using the event data as inputs to the machine learning model, a score indicative of a probability that the first cable system outage is repairable by a technician; and refrain from sending, by the cloud-based system, based on a comparison of the score to a score threshold, the event data to a first system associated with repairing the first cable system outage.