Network Tomography Partitioning Edge Effects
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Solution Overview
Problem
Traditional network analysis methods struggle to accurately assess and monitor the performance of complex data networks, especially for real-time applications like VoIP and video streaming, due to limitations in analyzing large networks and capturing dynamic behavior, as well as lack of access to all network components.
Innovation Solution
The use of network tomography techniques, including determining network topology, collecting traceroute data, and applying isotonic regression to partition end-to-end performance effects, allowing for the estimation and regularization of edge effects to improve network monitoring and analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional local queuing models are used at the individual router level, then detailed network component analysis is possible, but the complexity and impracticality increase very rapidly when expanding to moderately sized networks due to the large number of potential interactions
Solution Approach 1:
The patent segments the end-to-end network performance into individual edge-level effects by using network tomography to decompose aggregate measurements into component contributions. This allows detailed analysis of individual routers and network segments without requiring a complete complex model of all network interactions, thus achieving precise edge-level measurement without proportional increases in model complexity.
Solution Approach 2:
The patent introduces network tomography as an intermediary technique that acts as a mediator between end-to-end performance measurements and individual edge-level analysis. This intermediary method enables the extraction of edge-level information from aggregate measurements without requiring direct access to or detailed modeling of all network components, thus reducing the complexity burden while maintaining measurement precision.
2Adaptability or versatility
If network size increases to accommodate more applications and users, then network capability and coverage improve, but the ability to perform detailed performance analysis decreases due to the limitations of traditional modeling approaches
Solution Approach 1:
The patent enables the network monitoring system to self-serve by using automatically collected end-to-end performance data to infer edge-level conditions without requiring manual configuration or detailed knowledge of each network component. This self-service approach allows detailed performance analysis to scale with network size, as the system automatically adapts to larger networks without proportionally increasing analysis complexity.
3Productivity
If end-to-end performance measurements are used for network analysis, then overall network performance assessment is possible, but the ability to locate specific problems and assess detailed network performance at edge level is limited
Solution Approach 1:
The patent applies segmentation by decomposing end-to-end performance measurements into individual edge-level contributions using network tomography. This segmentation allows the system to maintain the efficiency of aggregate end-to-end monitoring while simultaneously achieving precise edge-level performance measurement, thus resolving the contradiction between assessment efficiency and measurement precision.
Data Source
AI summary
Systems and methods are presented for partitioning end-to-end performance effects using network tomography. In one embodiment, a method for partitioning end-to-end performance effects within a network is presented. The method includes determining a network topology between at least two test points, obtaining an unrelated approximation of edge effects between the test points, measuring end-to-end performance data between the test points corresponding to a target application, regularizing an estimate of edge effects for the target application using the unrelated approximation of edge effects, and computing the estimate of edge effects for the target application to partition the end-to-end effects.