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Reinforcement-Learning-Challenge-Optimizing-Bandwidth-Allocation-for-Satellite-Broadband-Users

by @Faycal214

Active 18

This repository features my solution for the DevFest '24 Challenge by @GDGAlgiers , where I used Proximal Policy Optimization (PPO) to optimize bandwidth allocation based on user demands over 24 hours. Key highlights include dynamic resource allocation and visualizations of demand versus allocation cycles

About this project

Hacker Guide The DevFest Algiers hackathon is primarily associated with university students from different technical backgrounds: programmers, ethical hackers, and software coders. It is a place where like-minded people come together to "hack" and craft realistic technical solutions. The goal of this year’s edition of Devfest Algiers Hackathon is to come up with a solution related to the theme of the edition during the event and to create functional software products by the end of the event. The hackathon has two phases, where the online lasts for 2 days, and the onsite phase for further 2 days to the teams that qualify. The hackathon also includes a prize for the winning teams. First challenge: Reinforcement Learning Challenge: Optimizing Bandwidth Allocation for Satellite Broadband Users Introduction Welcome to the Optimizing Bandwidth Allocation for Satellite Broadband Users challenge! In today's digital age, providing high-speed internet over shared satellite bandwidth is a significant challenge. Operators must balance delivering an optimal customer experience with managing operational costs and system constraints.

From the project README on GitHub

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25 Sept 2025

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