Network Application Control Using PCE Telemetry Feedback
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Solution Overview
Problem
Path computation elements (PCEs) in networking systems make decisions without considering the performance of local versus remote path computation options or the impact on path computation element applications, leading to inefficient path selection and network degradation.
Innovation Solution
An embodiment combines application telemetry data with network data to enhance path computation, using closed-loop analysis for dynamic resource allocation, PCE server selection, and network design rules, predicting hypothetical scenarios, and adjusting admission control to optimize network performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If path computation decisions are made without considering application performance state, then decision-making simplicity is improved, but network performance deteriorates
Solution Approach 1:
The system implements feedback by continuously monitoring application performance state and using this information to dynamically adjust path computation decisions. The PCE receives telemetry data about application performance and uses this feedback loop to optimize path selection, resource allocation, and admission control, thereby resolving the contradiction between simple decision-making and reliable network performance.
Solution Approach 2:
The system transitions from static path computation decisions to dynamic decisions that adapt to changing application performance conditions. The PCE can modify path selection, resource allocation, and admission control in real-time based on monitored application state, allowing the system to maintain optimal performance while keeping decision logic manageable through automated adaptation.
2Ease of operation
If centralized PCE server selection is based on simple preference settings, then configuration simplicity is improved, but server performance utilization deteriorates
Solution Approach 1:
The system enables dynamic PCE server selection based on real-time performance monitoring rather than static preference settings. The load manager monitors application performance state and dynamically determines which PCE server should handle path computation requests, optimizing server utilization while maintaining simple configuration through automated performance-based routing.
Solution Approach 2:
The system implements feedback mechanisms where performance telemetry data from applications is used to inform PCE server selection decisions. The load manager receives feedback about application performance and uses this information to dynamically route requests to the most appropriate PCE server, thereby improving server utilization without complicating the configuration process.
3Speed
If path computation calculations do not consider application impact, then calculation speed is improved, but overall network performance deteriorates
Solution Approach 1:
The system performs preliminary actions by pre-monitoring and caching application performance telemetry data before path computation decisions are made. This allows the PCE to quickly access relevant performance information during path calculation without performing complex real-time analysis, thereby maintaining calculation speed while still considering application impact in the decision-making process.
Data Source
AI summary
In one example embodiment, at least one processor determines an impact of an event on a network to a network application based on network data and telemetry information of the network application. The telemetry information of the network application is obtained from the network application placed under conditions corresponding to the event. The at least one processor adjusts operation of the network application based on the impact.