Using Machine Studying

Abstract: The Gamer's Personal Network (GPN) is a shopper/server expertise created by WTFast for making the community efficiency of online games faster and extra dependable. GPN s use middle-mile servers and proprietary algorithms to better join online video-sport gamers to their game's servers throughout a large-area network. On-line video games are a massive leisure market and community latency is a key side of a participant's aggressive edge. This market means many various approaches to community architecture are carried out by totally different competing corporations and that these architectures are continuously evolving. Ensuring the optimum connection between a shopper of WTFast and the net sport they wish to play is thus an incredibly troublesome downside to automate. Using machine learning, we analyzed historic community knowledge from GPN connections to discover the feasibility of community latency prediction which is a key a part of optimization. Our subsequent step can be to gather live data (together with shopper/server load, packet and port information and specific sport state information) from GPN Minecraft servers and bots. We will use this data in a Reinforcement Studying mannequin along with predictions about latency to change the clients' and servers' configurations for optimum community performance. These investigations and experiments will enhance the quality of service and reliability of GPN systems.

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