Reduction of Monitoring Register on Software Defined Networks

TL;DR

This paper presents a method using wavelet transforms to reduce monitoring register data in software-defined networks, maintaining essential information for effective anomaly detection.

Contribution

It introduces a novel approach to compress network monitoring data while preserving critical information for anomaly detection in SDNs.

Findings

Reduced monitoring register retains key information

Wavelet-based characterization improves anomaly detection efficiency

Method enhances data handling in high-traffic SDNs

Abstract

Characterization of data network monitoring registers allows for reductions in the number of data, which is essential when the information flow is high, and implementation of processes with short response times, such as interchange of control information between devices and anomaly detection is required. The present investigation applied wavelet transforms, so as to characterize the statistic monitoring register of a software-defined network. Its main contribution lies in the obtention of a record that, although reduced, retains detailed, essential information for the correct application of anomaly detectors.