Multicast Flow Anomaly Identification via Query Agent
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Solution Overview
Problem
Identifying and rectifying anomalies in multicast flow paths across complex networks is challenging due to the manual configuration of routers and potential errors, which can lead to misconfigured unicast settings, causing missing multicast data flows.
Innovation Solution
A query agent is implemented to generate a flow tree by querying routers, identifying anomalies by comparing data from various tables, and applying corrective configurations to misconfigured routers without requiring additional software or hardware modifications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual configuration of routers is used for multicast flow paths, then network setup flexibility is maintained, but configuration errors occur leading to missing multicast data flows
Solution Approach 1:
The system performs self-diagnosis by automatically querying router configurations and comparing them against the multicast flow tree to identify anomalies without requiring manual intervention. The query agent autonomously detects configuration errors and generates rectification recommendations.
Solution Approach 2:
The system implements a feedback mechanism where the query agent continuously monitors router configurations and multicast flow status, compares actual performance against expected behavior defined in the flow tree, and triggers automatic anomaly detection and rectification processes when deviations are detected.
2Reliability
If automated anomaly detection is implemented by querying each router, then multicast flow path reliability is improved, but system complexity increases
Solution Approach 1:
The query agent is designed as a universal tool that can query multiple types of router configurations and tables (routing tables, forwarding tables, interface configurations) across different router models and network locations, making it adaptable to various network topologies without requiring specialized detection mechanisms for each scenario.
3Measurement precision
If comprehensive router querying is performed to identify anomalies, then detection precision is improved, but processing time increases
Solution Approach 1:
The system performs preliminary actions by pre-defining the expected multicast flow tree structure and router configuration parameters before actual anomaly detection begins. This allows the query agent to efficiently compare actual router states against predetermined expectations, reducing the time needed for comprehensive querying while maintaining high detection precision.
Data Source
AI summary
An example system includes a network having interconnected routers, a multicast source to transmit data through the network for receipt by receiving host devices, and a query agent communicatively coupled to each router of the interconnected routers. The query agent is to generate a flow tree for multicasting of the data from the multicast source to each receiving host device, the flow tree including flow paths from the multicast source to each receiving host device, query each router to determine a status of at least one flow path of the flow tree, and identify an anomaly associated with at least one router in the at least one flow path.