STM Journals Peer-reviewed research from Consortium e-Learning Network

Journal of Advances in Shell Programming

Open Flow Network Visualization Software

  1. Vikas Bandaru
  2. K. Nikitha
  3. B. Amrutha Rao

Abstract

Traditional IP network infrastructure is merely static, rather than flexible. Due to the advent of Cloud technologies, future networks of machine-to-machine (M2M)/Internet of Things (IoT) and the mobile devices generating Big Data, it has become very difficult for network managers to configure and monitor the ever-changing network dynamically. Recently, the concept of Software-Defined Network (SDN), which allows us to administer and configure a network in a centralized and programmable manner, has gathered network engineers’ and researchers’ attention rapidly. OpenFlow has opened the door for network management in a more controlled way. Though OpenFlow controllers provide a lot of raw data collected from the underlying flows, it is still difficult for network managers to do analysis of that Big Data and take better decisions for the network. This research aims to realize a visualization software that facilitates the network managers to analyze the flow data in a more user-friendly way. The proposed tool helps us to visually identify selected flows from all lists of flows (i.e., Flowspace) and to monitor the status of selected flows through application-specific interactive visual representations.

Keywords

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