Network Segment Isolation via Synthetic TTL Tracing
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Solution Overview
Problem
Current tools face challenges in accurately isolating network segments affecting application performance, leading to inaccuracies and increased time to determine the root cause of issues, as they require manual stitching of data between applications and networks.
Innovation Solution
An agent process generates synthetic workload packets with incremental TTL values to identify isolated network segments by tracing traffic 'hop-by-hop' and encapsulating node IDs and metrics, allowing for automated detection and reporting of contributing network segments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual stitching of data between application and network is performed, then data collection can be achieved, but accuracy decreases and time to determine root cause increases
Solution Approach 1:
The patent segments the network path into discrete network segments by using TTL-based packet tracing. Each packet incrementally increases its TTL value to probe different segments along the communication path, allowing automated identification and isolation of specific network segments affecting application performance without manual data stitching.
Solution Approach 2:
The system performs self-diagnosis by automatically generating synthetic workloads and tracing network paths without requiring manual intervention. The agent process autonomously detects triggers, generates packets with incremental TTL values, receives TTL expiry error messages, and determines isolated network segments, eliminating the need for manual data collection and stitching operations.
2Measurement precision
If automated packet tracing with TTL increment is performed, then network segment isolation accuracy improves, but system complexity increases
Solution Approach 1:
The patent implements nested packet structures where synthetic workload packets contain encapsulated data fields that include node IDs and network metrics. This nested structure allows the system to trace multiple levels of network segments within a single packet framework, managing complexity through hierarchical organization of tracing information.
Solution Approach 2:
The system manages complexity by systematically changing the TTL parameter across packet iterations. By incrementing TTL values and observing TTL expiry error messages, the system automatically identifies network segments without requiring complex processing logic, as the TTL mechanism inherently provides segment isolation through parameter evolution.
3Extent of automation
If synthetic workload packets with incremental TTL are transmitted, then automated network segment detection is achieved, but network bandwidth consumption increases
Solution Approach 1:
The patent applies partial action by transmitting packets with incrementing TTL values only as needed for diagnostics, rather than continuous full-bandwidth traffic. The synthetic workload packets are sent selectively to trigger TTL expiry responses at specific network segments, achieving automated detection with minimal bandwidth consumption compared to full application traffic analysis.
Data Source
AI summary
In one embodiment, an agent process produces synthetic packet traffic and iteratively performs a sub-process that determines isolated network segments of the communication channel between intermediate nodes and computes a set of network metrics for the isolated network segments based at least in part on incrementing TTL expiry error data points. The sub-process also encapsulates, for inclusion within the next packet to be sent, a list of intermediate node IDs along the communication channel up to a latest received node ID and computed sets of network metrics for respective network segments. The agent process may then generate, upon termination of the sub-process, a report, the report including the list of intermediate node IDs along the communication channel up to a latest received node ID and computed sets of network metrics for respective network segments.