Interactive network active-traffic visualization (INAV) is a monitoring solution for use in real-time network environments, and is unique such that it only monitors the traffic that is currently active between nodes within a network and affords an intuitive visualization of that information - which consists of multiple layers of information/interaction. Several considerations exist that must be considered for this choice of research: to investigate and explore the problems and solutions associated with the visualization of large graphs amounts of data. Also to visualize the collected information without the problem of overwhelming the user, and particularly important is how to visualize the network infrastructure in real-time. Additionally, INAV is a useful tool designed for use by network administrators for the discovery of network traffic trends and behavior. This is relevant as the network administrator is responsible for the reliability and traffic between network segments, which is collected by utilizing passive scanning techniques.
There are two application that makeup INAV, the server and the UI. The server is responsible for collecting traffic and sending it to the UI module (the client) which will consist of a graph in which the nodes are associated with IP addresses, and the edges represent the traffic between those two nodes. As traffic is collected, new nodes will emerge, and their associated traffic (the edges) will become thicker and change in hue/saturation, as to represent the throughput of traffic between those nodes (figure 1). This will also be interactive, so that feedback will be provided to the user at different layers of information: computer/router, traffic data types, and the active network infrastructure.
By providing this information in real-time and on-demand the network administrator will be able to evaluate health diagnostics of the network and discover network traffic/routing trends. This is important as the efficiency and robustness of a network depends on the proper configuration of equipment in order to suit current traffic needs. The important processes in our research are the dynamic, interactive visualization coupled with real-time active statistics of network traffic. This bridges an already existing gap between "snapshot" network dataflow graphs and real-time packet sniffing applications.