Gamers Private Network Performance Forecasting. From Raw Data to the Data Warehouse with Machine Learning and Neural Nets
Abstract
Gamers Private Network (GPN) is a client/server technology that guarantees a connection for online video games that is more reliable and lower latency than a standard internet connection. Users of the GPN technology benefit from a stable and high-quality gaming experience for online games, which are hosted and played across the world. After transforming a massive volume of raw networking data collected by WTFast, we have structured the cleaned data into a special-purpose data warehouse and completed the extensive analysis using machine learning and neural nets technologies, and business intelligence tools. These analyses demonstrate the ability to predict and quantify changes in the network and demonstrate the benefits gained from the use of a GPN for users when connected to an online game session.
Cite
@article{arxiv.2107.00998,
title = {Gamers Private Network Performance Forecasting. From Raw Data to the Data Warehouse with Machine Learning and Neural Nets},
author = {Albert Wong and Chun Yin Chiu and Gaétan Hains and Jack Humphrey and Hans Fuhrmann and Youry Khmelevsky and Chris Mazur},
journal= {arXiv preprint arXiv:2107.00998},
year = {2021}
}
Comments
8 pages, 12 figures