Network Service Inference for Traffic Simulation
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Solution Overview
Problem
Network service providers face challenges in managing virtual private networks (VPNs) due to the diverse nature of hardware and protocols, making it difficult to guarantee quality of service (QoS) contracts, and there is a need for effective systems and methods to manage and infer services on networks.
Innovation Solution
The system receives topologically relevant network information, resolves conflicts, determines and stores network topology, and infers services based on the stored topology, allowing for the simulation of network performance and traffic generation to represent actual traffic patterns.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If diverse hardware and protocols are used to build VPN services, then service versatility and adaptability are improved, but device complexity and difficulty of management increase
Solution Approach 1:
The patent introduces a service inference system that acts as an intermediary between diverse network hardware/protocols and the management plane. This system automatically discovers services by analyzing network traffic patterns and topology, translating complex multi-vendor configurations into manageable service-level information without requiring manual intervention for each diverse component
Solution Approach 2:
The system enables self-service by automatically inferring service characteristics, topology, and performance metrics without human intervention. The service inference engine autonomously monitors network traffic, identifies service patterns, and maintains an updated view of VPN services across diverse hardware, eliminating the need for manual service configuration and tracking
2Productivity
If manual service management is used, then device complexity is reduced, but productivity and measurement precision of service quality deteriorate
Solution Approach 1:
The patent implements continuous feedback loops where the service inference system monitors network traffic, compares actual performance against inferred service characteristics, and automatically updates service models. This real-time feedback enables both high productivity through automation and precise measurement of service quality metrics such as bandwidth, latency, and packet loss
Solution Approach 2:
The system replaces manual mechanical service management with automated electronic inference mechanisms. Instead of manually configuring and monitoring services, the system uses intelligent algorithms to automatically discover service patterns, measure performance metrics with high precision, and adapt to changing network conditions, simultaneously improving productivity and measurement accuracy
3Measurement precision
If network topology information is collected and resolved, then measurement precision of service inference is improved, but loss of time for information processing increases
Solution Approach 1:
The patent applies preliminary action by pre-processing and normalizing network topology information as it is collected. The service inference system prepares data structures, resolves conflicts, and organizes topology information in advance, so that when service inference is needed, the data is already in a usable format, reducing processing time while maintaining high precision
Solution Approach 2:
The system segments the network information processing into distinct modules: topology discovery, conflict resolution, service pattern recognition, and performance measurement. This segmentation allows parallel processing of different information types and reduces overall processing time while maintaining comprehensive and precise service inference through coordinated module operation
Data Source
AI summary
Systems and methods are disclosed for simulating network performance. In one exemplary embodiment, the method includes inferring one or more services on the network; collecting network information based on actual traffic on the network; determining a traffic generator, such that the traffic generator represents the actual traffic on the network from a perspective of at least one of the inferred services; and simulating performance of the network using the determined traffic generator and at least one of the inferred services.