Manifold Structure Analysis of Tactical Network Traffic Matrix Based on Maximum Variance Unfolding Algorithm
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Manifold learning
Maximum Variance Unfolding (MVU) algorithm
Nonlinear dimensionality reduction



Submitted : 2023-10-30
Accepted : 2023-11-14
Published : 2023-11-29


As modern weapons and equipment undergo increasing levels of informatization, intelligence, and networking, the topology and traffic characteristics of battlefield data networks built with tactical data links are becoming progressively complex. In this paper, we employ a traffic matrix to model the tactical data link network. We propose a method that utilizes the Maximum Variance Unfolding (MVU) algorithm to conduct nonlinear dimensionality reduction analysis on high-dimensional open network traffic matrix datasets. This approach introduces novel ideas and methods for future applications, including traffic prediction and anomaly analysis in real battlefield network environments.


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