A QoE-Oriented Computation Offloading Algorithm based on Deep Reinforcement Learning (DRL) for Mobile Edge Computing (MEC) | This algorithm captures the dynamics of the MEC environment by integrating the Dueling Double Deep Q-Network (D3QN) model with Long Short-Term Memory (LSTM) networks.

This advanced and complex project implements an AI-powered optimization system for 5G Open RAN networks. Using machine learning and deep learning, the system optimizes network performance by detecting anomalies, predicting network traffic, and dynamically allocating resources.

Neural Network Hyper-parameter Tuning with Genetic Algorithms 🤖 🧬

A tool box for deploy time structure optimization for some modern CNN structures

GPU implementation of Floyd-Warshall and R-Kleene algorithms to solve the All-Pairs-Shortest-Paths(APSP) problem on Graphs. Code includes random graph generators and benchmarking/plotting scripts.

EcoSphereAI is a sustainable, AI-driven platform optimizing connectivity systems with features like energy optimization, predictive maintenance, and sustainability reporting. Build the future of efficient and green networks!

Network optimization problem solved using Gurobi Python

A synthetic digital twin of a retail supply chain network, simulating the optimization model annual refresh process used by large retailers (Home Depot, Walmart, Lowe’s, Amazon) to guide long-range supply chain investments and explore cost, service and scenario tradeoffs. [Website is frontend only, DB is stored locally in SQLite]

This repository represents Multi-Factory Network Scheduling MILP optimizer using Python language

🚀 Transform your internet speed without changing ISP. BBR-like TCP optimizations + intelligent network failover + DNS protection for Windows/Linux

A Flask application for managing Quality of Service (QoS) policies on network devices. Provides web-based interface for configuring and monitoring QoS settings.

4 sample solutions on Network optimization problems.

[ToN 2024] On the Benefits of Traffic “Reprofiling” the Multiple Hops Case—Part I

This repository contains the tools and results developed for my undergraduate thesis (TCC) in Computer Science at UFES São Mateus. The project focuses on analyzing and improving Wi-Fi coverage on campus through network mapping, custom measurement tools, and advanced router placement simulations. All solutions are data-driven and open-source.

Python simulation of the London Underground network that finds the fastest route between stations using weighted graph algorithms. Includes dynamic connections and optimization for travel time and network efficiency.

Multi-stage Stochastic Programming for Integrated Network Optimization in Hurricane Relief Logistics and Evacuation Planning

A variant of neuroplan that uses synthesized datasets (based on the Topology Zoo)