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Abstract: The Gamer's Non-public Community (GPN) is a consumer/server know-how created by WTFast for making the network performance of online games quicker and more dependable. GPN s use middle-mile servers and proprietary algorithms to raised connect on-line video-recreation gamers to their game's servers across a large-area community. On-line video games are a large entertainment market and network latency is a key facet of a participant's aggressive edge. This market means many various approaches to community architecture are carried out by different competing corporations and that those architectures are consistently evolving. Making certain the optimal connection between a consumer of WTFast and the net game they want to play is thus an extremely troublesome downside to automate. Using minecraft crafting learning, we analyzed historic community data from GPN connections to explore the feasibility of network latency prediction which is a key part of optimization. Our subsequent step will probably be to gather reside data (together with shopper/server load, packet and port info and particular recreation state information) from GPN Minecraft servers and bots. We will use this info in a Reinforcement Learning model along with predictions about latency to alter the shoppers' and servers' configurations for optimal network efficiency. These investigations and experiments will enhance the standard of service and reliability of GPN techniques.
