| Title | : | A Neural Network-based network selection for QUIC to enrich gaming in NextGen Wireless networks |
| Speaker | : | Madhan Raj Kanagarathinam (IITM) |
| Details | : | Tue, 28 Nov, 2023 3:30 PM @ SSB-334 |
| Abstract: | : | The surge in popularity of online gaming, particularly on smartphones, underscores the growing trend and demand for immersive gaming experiences. Online smartphone gaming faces challenges such as poor Wi-Fi conditions and network handovers, impacting user experiences. In response, we propose ODIN (On-Device Intelligence), a Neural Network-driven and QUIC transport layer protocol based gaming proxy to enrich the users' Quality of Experience (QoE). ODIN integrates a sophisticated NN-based network quality monitoring framework to predict Wi-Fi contention accurately, ensuring optimal network selection for gaming applications and minimizing lags. Live-air experiments featuring popular Android gaming applications (such as BrawlStars) confirm ODIN's superiority over legacy smartphones. It surpasses Multipath TCP (MPTCP) in handling thin-stream applications, showcasing a seamless zero-touch, zero-lag handover mechanism in the BrawlStars game. Evaluation results demonstrate ODIN's consistent provision of superior gaming QoE while optimizing mobile data usage. Dynamic selection of the best network interface, guided by NN-based predictions, ensures seamless handover between Wi-Fi and mobile networks, contributing to efficient network resource utilization and significant savings in mobile data consumption. In addition to robust performance, ODIN introduces ODIN-LITE, a lightweight variant exhibiting a remarkable 25% improvement in power consumption efficiency compared to MPTCP's full-mesh mode. ODIN enhances gaming Quality of Experience (QoE) across diverse network conditions. |
