Big Data and IT Network Data Visualization

Lidong Wang

doi:10.33889/ijmems.2018.3.1-002

Abstract

Visualization with graphs is popular in the data analysis of Information Technology (IT) networks or computer networks. An IT network is often modelled as a graph with hosts being nodes and traffic being flows on many edges. General visualization methods are introduced in this paper. Applications and technology progress of visualization in IT network analysis and big data in IT network visualization are presented. The challenges of visualization and Big Data analytics in IT network visualization are also discussed. Big Data analytics with High Performance Computing (HPC) techniques, especially Graphics Processing Units (GPUs) helps accelerate IT network analysis and visualization.

Highlights

The purpose of this paper is to present advances of Information Technology (IT) network visualization, especially Big Data analytics in IT network visualization
The capability of providing multiple views of the same or related data is significant for achieving multiple views and levels of data
Network intrusion detection methods based on graphs are useful approaches to the visualization of network intrusion

Summary

Introduction

Data can be generally represented using graphs including curves and bar charts or pie charts. Data mining supports knowledge discovery by creating models, classifying and predicting, finding associations or hidden patterns, and visualizing the data mining results using tools. With visualization tools in genetic data analysis, the interactions among complex biological structures, and alignments among genomic or proteomic sequences are very efficiently represented in the forms of graphs, transformed into different types of visual displays that are easy to be understood. Visual data mining and visualization have become very important in the analysis of biological data (Han and Kamber, 2006)

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Methods

Conclusion