Multi-Hop Network Performance Management via Segmented Telemetry
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Solution Overview
Problem
In multi-hop network topologies, it is challenging to determine the root cause of poor session performance across various elements, such as client devices, gateway services, and cloud connectors, due to the complexity of network paths and multiple administrators involved, making it difficult to identify and remediate performance issues effectively.
Innovation Solution
A system and method that collect and process values for various factors associated with each hop in the network topology, using heuristics and telemetry data to identify performance issues and determine the specific elements causing degradation, allowing for targeted actions to improve session responsiveness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple hops and elements are used to provide session services, then service coverage and accessibility are improved, but performance troubleshooting and root cause identification become more difficult
Solution Approach 1:
The patent segments the multi-hop network into discrete hops and identifies specific elements within each hop (gateway service, cloud connector, infrastructure). By collecting telemetry data for each segmented component separately, the system can isolate performance issues to specific segments rather than treating the entire network as a single undifferentiated system.
Solution Approach 2:
The patent introduces an intermediary performance management system that collects telemetry data from multiple sources (clients, gateways, cloud connectors, infrastructure) and processes this data to identify root causes. This intermediary system acts as a mediator between the complex multi-hop network and the troubleshooting process, translating raw telemetry into actionable insights about which specific element is causing performance degradation.
2Measurement precision
If comprehensive telemetry data is collected from all hops and elements, then root cause identification accuracy is improved, but system complexity and data processing requirements increase
Solution Approach 1:
The patent implements a universal telemetry collection framework that uses standardized data collection mechanisms across all hops and elements (clients, gateways, cloud connectors, infrastructure). This multi-functional approach allows the same collection infrastructure to gather diverse performance metrics from different network components, reducing overall system complexity despite the comprehensive nature of data collection.
Solution Approach 2:
The patent establishes feedback loops where telemetry data is continuously collected, analyzed, and used to identify performance issues. The system provides feedback about which elements are causing problems and triggers appropriate remediation actions. This feedback mechanism transforms the complex data collection process into a manageable iterative cycle of measurement, analysis, and correction.
3Productivity
If automated actions are taken to remediate performance issues, then session performance recovery is improved, but risk of incorrect actions increases
Solution Approach 1:
The patent implements preliminary actions by first collecting and analyzing telemetry data to identify the root cause before executing remediation actions. The system determines which specific element is causing performance degradation and selects appropriate actions based on this preliminary analysis. This ensures that automated actions are targeted and accurate rather than random or guesswork-based.
Solution Approach 2:
The patent enables self-service automation where the performance management system automatically monitors its own health, identifies issues, and executes remediation actions without human intervention. The system can automatically reboot elements, scale resources, or reroute traffic based on detected performance problems, improving recovery speed while maintaining reliability through algorithmic decision-making based on established performance thresholds and patterns.
Data Source
AI summary
Managing performance of elements providing a session via a multi-hop network topology is provided. A system receives values for factors associated with elements that form hops in a multi-hop network topology. The system determines a performance metric for each hop using the values for one or more factors selected from the factors. The system identifies a hop of the hops as having a performance issue based on the performance metric for the hop exceeding a threshold. The system selects, responsive to the performance metric of the hop exceeding the threshold, an action to take on at least one element forming the hop.