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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.
🌐 Scripts to configure persistent MTU settings for Tailscale on Linux and Windows, enhancing network performance with automated and customizable setups.
Constrained optimization problems, including linear,network, dynamic,integer, and nonlinear programming, decision trees, queueing theory and Markov decision processes.
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.
A tool for testing and optimizing Cloudflare IPs using ITDOG nodes across Chinese ISPs, automatically selecting best-performing IPs and updating Cloudflare Worker configuration.
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.
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.