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scor

Software-defined Constrained Optimal Routing (SCOR) is a northbound interface for SDN (Software Defined Networking) which can be used with any SDN controller for creating QoS Routing applications based on Constraint Programming

sdn

SDN project based on ryu and mininet

sdn-1

Software-defined Networking "Implementation of measurement-based QoS mechanisms"

sdn-app

这个目录中存放的是自己学习SDN时写的mininet拓扑结构和Ryu应用程序。

sdn-drl

sdn-mininet-programs

Implementation of RYU based Software Defined Networks using Mininet

sdn-pox-controller-for-mininet-with-qos-and-firewall

SDN POX Controller with QoS and Firewall implemented for Mininet

sdn-qos

Implementation of quality of service and call admission control features within sdn network. This implementation uses Ryu Framework (https://ryu-sdn.org/) to develop controller applications based on OpenFlow v1.3

sdn-qos-routing

sdn-routing-ryu

Using Dijkstra's algorithm for a SDN network routing. The network is simulated by Mininet and the routing algorithm is written with Ryu SDN framework

sdn-ryu-mininet-path

Mix of files

sdn-simulation

Reproduce the Simulation for Software Defined Network(SDN) based on Omnetpp-5.4.1 and Reinforcement Learning Algorithm in paper "QoS-Aware Adaptive Routing in Multi-layer Hierarchical Software Defined Networks: A Reinforcement Learning Approach"

sdn-with-mininet-wifi

QoS analysis of SDN using Mininet Wifi and Ubuntu

sdn_qos

This is my master's thesis project: "QoS implementation in Software Defined Network using Ryu Controller"

sdn_qos_multiplex_infocom21

Synthetic experiments for SDN QoS multiplexing project used in INFOCOM'21 paper

sdn_shortest_path

Shortest path experiment of SDN, using RYU as controller and mininet. The topology is a simple fat tree.

sr-gnn

[AAAI 2019] Source code and datasets for "Session-based Recommendation with Graph Neural Networks"

tf-gnn-samples

TensorFlow implementations of Graph Neural Networks

tf2-rl

Reinforcement learning algorithms implemented for Tensorflow 2.0+ [DQN, DDPG, AE-DDPG, SAC, PPO, Primal-Dual DDPG]

transportation-routes-optimization-by-rl

Application of reinforcement learning to Optimize transportation routes using reinforcement learning

tripple

RPL for {Linux, LWIP, Embedded OS}. A mesh routing protocol implementation designed to scale, yet resource optimal. Primary factor for optimization is to reduce network control overhead.

understanding-the-modeling-of-network-delays-using-nn

Recent trends in networking are proposing the use of Machine Learning (ML) techniques for the control and operation of the network. In this context, ML can be used as a computer network modeling technique to build models that estimate the network performance. Indeed, network modeling is a central technique to many networking functions, for instance

unveiling-the-potential-of-gnn-for-network-modeling-and-optimization-in-sdn

yet-another-simple-http-server-for-mininet

another not very simple fastapi server support video streaming, upload, download, server respone time and latency