Pinned Repositories
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平常使用过后剩下的算法
AppIdentificationHTTPS
论文"Mobile Application Identification Over HTTPS Traffic Based on Multi-view Features"程序
deep-SDN
End-of-Year Project, Intelligent SDN traffic classification using deep learning : classifying SDN network traffic to differentiate between normal and abnormal packets by detecting attacks using deep learning. Mininet - RYU - Tensorflow - Neural Networks - CNN
DeepTraffic
Deep Learning models for network traffic classification
dpdk-1
dpdk学习及相关项目
elephantFlowDetection
Elephant flow detection in SDN enabled networks
Graphml-To-Mininet
mininet-script
用于创建各种仿真网络的Mininet脚本
netcap
A framework for secure and scalable network traffic analysis - https://netcap.io
netem
在docker中部署OVS-DPDK作为网络交换节点，进行网络仿真
sinofeng's Repositories
sinofeng/Graphml-To-Mininet
sinofeng/netem
在docker中部署OVS-DPDK作为网络交换节点，进行网络仿真
sinofeng/awk
The AWK Programming Language (AWK 程序设计语言, awkbook) 中文翻译, LaTeX 排版
sinofeng/butterfly
Butterfly connects Virtual Machines and control their traffic flow
sinofeng/caching_project
implementation of cooperative caching algorithm for edge computing
sinofeng/deep-SDN-1
Intelligent SDN traffic classification using deep learning : Generating and classifying SDN network traffic to differentiate between normal and abnormal packets using deep learning.
sinofeng/doat
DPDK Optimisation & Analysis Tool
sinofeng/DPDK-TCP-UDP_Protocol_Stack
Simple protocol stack based on dpdk（使用dpdk搭建协议栈）
sinofeng/dperf
dperf is a DPDK based 100Gbps network performance and load testing software.
sinofeng/e15-4yp-Microservice-Based-Edge-Computing-Architecture
sinofeng/FogBus2
FogBus2: A Lightweight and Distributed Container-based Framework for Integration of IoT-enabled Systems with Edge and Cloud Computing
sinofeng/future-internet
Multiple projects about congestion control, adaptive bitrate streaming, topology design, and WAN traffic engineering.
sinofeng/GON
[NeurIPS-W'21] Generative Optimization Nets for Memory-Efficient Data Generation
sinofeng/iotg-dpdk-ref-app
sinofeng/Joint-Routing-and-Computation-2022
Joint routing and computation scheduling in collaborative edge computing for heterogeneous network with arbitrary topology
sinofeng/l2fwd-nv
l2fwd-nv provides an example of how to leverage your DPDK network application with the NVIDIA GPUDirect RDMA techonology.
sinofeng/LoRaWANGatewayDeviceCoordinationProtocol
A Gateway-Device Coordination Protocol for enabling Edge Computing over LoRaWAN developed as part of my Master Thesis @ Sapienza University of Rome
sinofeng/LyDROO
Lyapunov-guided Deep Reinforcement Learning for Stable Online Computation Offloading in Mobile-Edge Computing Networks
sinofeng/Machine_Learning_Code_Implementation
Mathematical derivation and pure Python code implementation of machine learning algorithms.
sinofeng/Malcolm
Malcolm is a powerful, easily deployable network traffic analysis tool suite for full packet capture artifacts (PCAP files) and Zeek logs.
sinofeng/ndn-dpdk
NDN-DPDK: High-Speed Named Data Networking Forwarder
sinofeng/Oddlab
Oddlab DCN traffic engineering and fault-tolerant method repo.
sinofeng/poseidon
Poseidon is a python-based application that leverages software defined networks (SDN) to acquire and then feed network traffic to a number of machine learning techniques. The machine learning algorithms classify and predict the type of device.
sinofeng/PureEdgeSim
PureEdgeSim: A simulation framework for performance evaluation of cloud, fog, and pure edge computing environments.
sinofeng/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.
sinofeng/SDN_load-prediction-and-balancing
基于LSTM的SDN流量预测与负载均衡
sinofeng/Traffic-matrix-prediction-1
SDN traffic matrix prediction with LSTM
sinofeng/trex-scripts
Benchmarking setup for plotting latency and jitter using TRex for traffic generation and DPDK for hardware acceleration.
sinofeng/websocket-for-data-transmission
This websocket program is for data transmission between server and client. Data transmission is for Federated Learning in Edge computing environment.
sinofeng/yomo
🦖 Serverless Streaming Framework for Low-latency Edge Computing applications, running atop QUIC protocol, as Metaverse infrastructure, engaging 5G technology and Geo-distributed System.