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pytvn

A suite to analyze Time-Varying-Networks within the Activity-Driven framework featuring reinforcement process and burstiness.

qos-floodlight

Based floodlight official website qos project,my env is sdnhub vm with ovs 2.1.0 version and openflow1.3 and it works

queue_management-and-bandwidth-control-sdn

qvegas

TCP Qvegas is very well!

redeo

High-performance framework for building redis-protocol compatible TCP servers/services

reflow

re:Flow - Multi-purpose work flow processing engine for JVM,Android,IoT and Edge Computing

reliable-udp

This project adds TCP like functionality of sequence numbers, re-transmission and timeouts, flow control and congestion control using UDP sockets

reliable-udp---congestion-and-flow-control

The project implements the congestion and flow control in UDP (User Datagram Protocol) to make the transmission reliable without including the cost of three way handshaking. Congestion control is implemented using TCP Tahoe Algorithm.

reloc

Data-analysis-enabled Notification Generation and Delivery System for Edge Computing

resources-allocation-in-the-edge-computing-environment-using-reinforcement-learning

Simulated the scenario between edge servers and users with a clear graphic interface. Also, implemented the continuous control with Deep Deterministic Policy Gradient (DDPG) to determine the resources allocation (offload targets, computational resources, migration bandwidth) in the edge servers

ride

Resilient IoT Data Exchange (RIDE) using SDN and edge computing. This repository includes the algorithms, prototype implementation, SDN controller REST API adapter, and Mininet-based experimental framework we used to evaluate its performance.

risk_aware_mec_offloading

Code for Data Offloading in UAV-assisted Multi-access Edge Computing Systems: A Resource-based Pricing and User Risk-awareness Approach paper https://www.mdpi.com/1424-8220/20/8/2434/pdf

rtsp_deep_packet_inspection-master

This is an rtsp packet depth inspection tool, whose main functions include traffic sniffing, RTSP protocol identification, RTSP packet depth inspection, and media stream aggregation based on RTSP sessions. The specific steps are to identify the RTSP traffic from the sniffed traffic, and extract the relevant media stream transmission information from the RTSP traffic to store in the mysql database. For non-rtsp streams, determine whether it is based on the address information (ip: port) retrieved from the database Media streaming. The aggregation of media streams has two main purposes. One is to perform targeted anomaly detection on the aggregated media streams, but to perform anomaly detection on the non-media streams of the camera. After the media streams are independent, the detection will be improved Precision and efficiency, which are the ultimate goals of this project, are currently being completed.

rudp

In this project, we have developed a library for Reliable UDP, which enables the application using it to send multiple files to multiple destinations. The library inserts a RUDP header on the payload of normal UDP datagram by which a reliable transmission can be achieved. It does the flow control using Go-Back-N ARQ sliding window technique same as in TCP, but in contrast RUDP doesn’t provide congestion control, error recovery and other TCP capabilities. RUDP has its application in the scenarios where user do not want to add more overhead to the data (as like in TCP header of 20 bytes), but requires overall reliable data transfer.

rulex

Rulex is a RuLE-LEX framework for edge computing (so called fog-computing), support various data sources and data flows. Rulex is designed to process data streams fast and reliable with IoT southern gateways.

ryu

Network traffic classification using ML/DL and multipath transmission based on SDN.

ryu_multipath

multipath transmission in SDN

scission

A Tool for Maximising Performance of Deep Neural Networks in Edge Computing

sdn-based-network-firewall

Software-based firewall that direct traffic on a network taking rules set up dynamically

sdn-based-network-traffic-anomaly-detection-model-design-and-implementation

SDN-based network traffic anomaly detection model design and implementation

sdn-congestion-control

A software defined network that identifies, and throttles high bandwidth connections

sdn-controller-for-mobile-edge-computing-relying-on-openairinterface

This repository contains two python codes that play a big role in the traffic redirection in Mobile Edge Computing (MEC). RYU controller is in charge of the traffic redirection. The main application is written in sdn_mec2_ryu.py, and the other code (Northbound_RYU.py) is responsible for the northbound API calls coming from the Mobile Edge Computing Platform Frontend to the RYU controller.

sdn-data-with-lstm

Detect anomalies in SDN using LSTM

sdn-ddos-detection-and-mitigation-using-ml-and-statistical-methods

Programmed the SDN controller to monitor the traffic, predict the traffic behaviour and detect DDOS traffic in the cloud network and mitigate it. Machine learning SVM algorithm was used to predict the malicious traffic in the network, achieved an accuracy of 98% and detection rate of 100%. Technologies Used are, SDN, ML SVM, Openflow, Ryu controller, Python, Mininet, iperf, hping3, linux commands.

sdn-handbook

SDN手册

sdn-lstm-traffic-prediction

sdn-machinelearning-numberofflowsdetection

MasterThesis on Number of Flows Detection in SDN networks using Machine Learning

sdn-te-sr

SDN based Traffic Engineering and Segment Routing

sdn-te-sr-tools

tools for SDN based Traffic Engineering

sdn-tmprediction

The work in paper "An AI-based Traffic Matrix Prediction Solution for Software-Defined Network" - Duc-Huy LE, Hai Anh TRAN, Sami SOUIHI, Abdelhamid MELLOUK