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 simple guide to optimize your ping in CS2 through Windows Registry tweaks and in-game settings adjustments by @OhLasFar on Twitter.

🔍To choose the best CloudFront IPs for achieving fast⚡ and low-latency connections

🌐 Scripts to configure persistent MTU settings for Tailscale on Linux and Windows, enhancing network performance with automated and customizable setups.

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

Supply chain network optimization for oilseed processing (bio-diesel application)

Network Optimisation solver

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.

Constrained optimization problems, including linear,network, dynamic,integer, and nonlinear programming, decision trees, queueing theory and Markov decision processes.

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!

Master's Thesis: Dynamic Quality Estimation of Wireless Links with Autonomous Agents

Network optimization problem solved using Gurobi Python

Formulate the network optimization problem as a discrete model, identifying mathematically the variables and constraints associated with the network. Formulate (mathematically) and solve a non-linear optimization problem based on real (or realistic) world data.

Solving linear programming using python optimizer interface. This repo allows you to add multiple decision vars and constraints etc. in a very easy way.

Network-flows: a c++ command line tool for network optimization problems

In this project, I built several optimization models to determine production level, manage shipment, and maximize thesis points. I also built queueing models to analyze queueing systems in a hospital and made recommendations to meet the criteria, and simulation models to analyze system performance under uncertainty.

Implementation of 2 apps, using Mininet as a Virtual Network Simulator and OpenDaylight Software-Defined-Networking Controller.

A brief course intended to introduce non-programmers to python and data wrangling. Also, demonstration of network optimization, pdf creation in Python, and a simple Monte Carlo simulation.