Network Analyzer for Wide Area Network Topology Inference
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Solution Overview
Problem
Current systems for determining optimal routes in wide area networks across multiple autonomous systems lack efficient methods for analyzing network performance metrics and selecting routes that balance cost, bandwidth, and latency, leading to suboptimal data transmission.
Innovation Solution
A network analyzer gathers and processes performance metrics across multiple autonomous systems to generate a network topology model, assigning quality scores to routes, and a controller selects routes based on these scores to optimize data transmission, using techniques like load balancing and virtualization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If standard routing protocols are used in wide area networks, then routes can be established between autonomous systems, but the route selection is suboptimal and does not efficiently balance cost, bandwidth, and latency
Solution Approach 1:
The system implements feedback mechanisms by continuously collecting network performance metrics (bandwidth, latency, cost) from multiple autonomous systems and using this information to dynamically adjust route selections. The network analyzer receives real-time data about network conditions and feeds this back to the route selection process, enabling adaptive optimization rather than static routing decisions.
Solution Approach 2:
The patent applies dynamics by transitioning from static routing tables to dynamic route selection that adapts to changing network conditions. The system continuously monitors network metrics and adjusts route quality scores in real-time, allowing the routing behavior to evolve based on current bandwidth availability, latency variations, and cost changes across different autonomous systems.
2Reliability
If network performance metrics are collected and analyzed across multiple autonomous systems, then optimal route selection can be achieved, but the system complexity and computational requirements increase
Solution Approach 1:
The system segments the complex task of multi-autonomous system route optimization into distinct functional modules: a network analyzer component that collects and processes metrics, a route evaluation component that calculates quality scores, and a route selection component that makes decisions. This segmentation allows each component to handle specific aspects of the problem independently, reducing overall system complexity while maintaining comprehensive analysis capabilities.
Solution Approach 2:
The patent introduces a network analyzer as an intermediary component that mediates between raw network metrics from multiple autonomous systems and the route selection process. This intermediary aggregates, normalizes, and processes diverse metric data into standardized quality scores, simplifying the interface between metric collection and route decision-making while enabling comprehensive analysis without directly increasing the complexity of the core routing logic.
3Adaptability or versatility
If real-time network metrics are monitored and processed, then dynamic route adjustments can be made, but the computational overhead and processing time increase
Solution Approach 1:
The system applies partial action by selectively analyzing and adjusting routes based on current network conditions rather than continuously re-evaluating all possible routes. The network analyzer focuses computational resources on routes that are likely to benefit from optimization based on metric thresholds and change detection, performing full analysis only when necessary rather than continuously processing all route options.
Solution Approach 2:
The patent utilizes parameter changes by monitoring network metrics and adjusting route quality scores based on predefined thresholds and weighting parameters. When network conditions change beyond certain parameter thresholds (bandwidth variations, latency spikes, cost changes), the system dynamically recalculates quality scores with adjusted parameters, enabling adaptive response without continuous full re-evaluation of all routes.
Data Source
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AI summary
Described are methods and system for network analysis. A network analyzer for a first network is configured to receive network assessment information from a network metric monitors situated in third-party networks, the network assessment information indicating values for characteristics of one or more network paths from the respective network metric monitor to a node in a second network. The network analyzer aggregates the received network assessment information and identifies, from the aggregated network assessment information, a route from the first network to the node in the second network. The identified route is then selected from among a plurality of potential routes from the first network to the node in the second network and used in setting a routing policy for data flows from the first network through the node in the second network.