Distributed SDN controller built on top of beehive.

Distributed SDN Controller

Distributed SDN Controller

Implement a machine-learning based approach to detect Distributed Denial of Service (DDoS) attacks in the Software Defined Networking (SDN) paradigm. Data is created using mininet and pox controller.

Traineeship project. Implementation of distributed, flat SDN controllers that interact via east/west bound communication using Zenoh

addressing DoS attacks on distributed SDN controller architectures

Distributed update aware SDN Controller. Floodlight based.

TA Load Balancing untuk multiple controller pada SDN berbasis switches group dan distributed decision

The code for an SDN controller application that was used to write my undergrad thesis in computer networks and distributed systems. See readme for links to the paper and the poster it was later turned into and published at ICPE2020.

This code builds a load balancer based on the randomization algorithm and the Round Robin algorithm in networks to distribute the load and requests between servers in order to reduce the stress on the servers. These codes can be used as a load balancer app in SDN by downloading Mininet emulator and POX controller. Demo for project https://drive.google.com/file/d/1uI6iSUoxlBsRoGeJ9-gUY_t8MgeiWnfA/view?usp=sharing

A distributed SDN controller

distributed SDN controller writen in scala

Design Concept for a Failover Mechanism in Distributed SDN Controllers

A fault-tolerant, consistent and distributed SDN controller.

Distributed Controller monitoring and load balancing for SDN Control Plane

This project implements a Software-Defined Networking (SDN) edge cloud infrastructure integrated with Hadoop distributed computing capabilities. It combines SDN controllers (Ryu), OpenVSwitch (OVS) edge nodes, and a Hadoop cluster to create a flexible and manageable cloud computing environment.

This project focuses on enhancing Network Security in a Software Defined Networking (SDN) environment through the detection of Distributed Denial of Service (DDoS) attacks using Machine Learning (ML) techniques. Built on a simulation stack using Mininet, Ryu controller, and custom traffic generators.

Software-Defined Networking has been proven advantageous in terms of performance, manageability, and scaling for data centers. Still, when it comes to security, there is a loophole in the design of this new paradigm, which is its centralized structure. SDNcontroller is vulnerable to mainly Distributed Denial of Service (DDoS) attacks. If the controller becomes the victim of DDoS attack, it can become a severe problem to the whole network as it keeps entertaining the false requests coming from the attacker. Asa result, the controller becomes overloaded and will not be able to respond to genuine requests. Also, it will produce so many false flows that will be filled in the SDN switches, and as a result, the switches will be overloaded. Thus detection of DDoS attack becomes important for the security of Software Defined Networking. In this project, DistributedDenial of Service (DDoS) attacks have been detected using machine learning models. The datasets have been created using the sFlow-rt tool both for the normal traffic and the attack traffic, and then using these datasets, various machine learning models have been trained. The datasets were trained and tested with Multilayer Perceptron (MLP) and K-Nearest Neighbors (KNN) classifiers. From the results, we can conclude that machine learning methods can show better results in the detection of DDoS attack.

Distributed SDN Controller

TA SDN Distributed Controller

A new way to make SDN controllers distributed.

Distributed SDN controller built on top of beehive.

NIPS for DDoS attacks based on distributed SDN controller

LISP management plane project repository for ONOS distributed SDN controller.

LISP control plane project repository for ONOS distributed SDN controller.

A Distributed SDN Controller-Based Computing Framework for Effective In-Orbit Computing

A Software-Defined Networking (SDN) network utilizes Pox controllers, allowing them to communicate with each other through HTML requests. The primary objective of this network is to establish a smart parking system. Requests for parking lots are stored in a distributed blockchain, ensuring accessibility across all nodes which are the controllers.

This project investigates Distributed Denial of Service (DDoS) attacks targeting the control plane of Software-Defined Networks (SDN) using a POX controller. The attack is implemented by flooding the controller with malicious traffic, causing resource exhaustion and network service disruption.

Improve SDN architecture by introducing distributed system in which if a controller fails or becomes unstable, a signal will be sent to perform failover switch to another controller while maintaining network synchronization. This aims to provide redundancy, fault tolerance, and reliability within network systems.

hypercontroller is a SDN application that allows distributed deployment of POX (OpenFlow based controller) in a network, to improve performance and for fast failover. Works with a modified POX code to support hypercontroller <https://github.com/micheal-o/pox/tree/hctrl-compatible>.