Automatic Detection of Elephant flows through Openflow-based OpenvSwitch

Mallesh, Spurthi (2017) Automatic Detection of Elephant flows through Openflow-based OpenvSwitch. Masters thesis, Dublin, National College of Ireland.

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Abstract

Software Defined Networking (SDN) has proved its importance as it allows users to create a Virtual network with just a few lines of code. It provides a vision of the network with the control plane separated from the data plane and is managed centrally. It also enables easy integration of new functionalities. While SDN is rapidly spreading through the network industry, it still faces issues with managing, monitoring, and controlling the network centrally. One of the major issues faced is the monitoring of the traffic flowing in the network. As there is rapid growth in data, there is an increase in data flow in the network every day. This leads to traffic congestion, and monitoring the traffic is a challenging task. The traffic can be caused due to several reasons, and one of the major reasons is due to large flows. These large flows are known as Elephant flows. This paper proposes an algorithm to detect the elephant flows in an Openflow network automatically. This algorithm sets a predefined bandwidth for the flow, and if the bandwidth exceeds the limit, the flows are automatically captured and presented in the form of a graph. This project involves Open Flow controller, OpenvSwitch and Open Flow protocol. In SDN, Open Flow provides additional features to help in monitoring the traffic. Previously, a lot of efforts have been made in this field to improve the quality of the network. The prime focus in this project is to collect the flow details and detect the elephant flows in the network automatically. The analysis and the enhancements carried out in this project have proved to be a better detector of the elephant flows in the network.

Item Type:	Thesis (Masters)
Subjects:	Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Cloud computing
Divisions:	School of Computing > Master of Science in Cloud Computing
Depositing User:	Caoimhe Ní Mhaicín
Date Deposited:	21 Nov 2017 11:43
Last Modified:	21 Nov 2017 11:43
URI:	https://norma.ncirl.ie/id/eprint/2873

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