Utilizing Machine Learning


Summary: The Gamer's Personal Network (GPN) is a client/server expertise created by WTFast for making the network efficiency of on-line games sooner and extra dependable. GPN s use center-mile servers and proprietary algorithms to raised join on-line video-game players to their recreation's servers across a large-space community. On-line video games are an enormous entertainment market and community latency is a key side of a player's competitive edge. This market means many alternative approaches to network architecture are implemented by different competing corporations and that those architectures are continuously evolving. Guaranteeing the optimal connection between a client of WTFast and the online game they want to play is thus an incredibly troublesome problem to automate. Utilizing machine studying, we analyzed historical network data from GPN connections to discover the feasibility of community latency prediction which is a key part of optimization. Our next step will likely be to collect live knowledge (including shopper/server load, packet and port information and specific recreation state data) from GPNMinecraft serversand bots. We'll use this data in a Reinforcement Studying model along with predictions about latency to change the shoppers' and servers' configurations for optimum network efficiency. These investigations and experiments will improve the standard of service and reliability of GPN programs.