A Neural Network-Based Network Selection for QUIC to Enrich Gaming in NextGen Wireless Network

被引：0
|
作者：
Kanagarathinam, Madhan Raj [1 ,2 ]
Sivalingam, Krishna M. [2 ]
Lee, Sunghee [1 ]
机构：
[1] Samsung Elect, MX Dept, Suwon 16677, South Korea
[2] Indian Inst Technol Madras, Dept Comp Sci & Engn, Chennai 600036, India
来源：
IEEE TRANSACTIONS ON CONSUMER ELECTRONICS | 2024年 / 70卷 / 01期
关键词：
QUIC; QoS; online gaming; smartphones; Industry; 50; TCP;
D O I：
10.1109/TCE.2023.3335092
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
Online gaming on smartphones is increasingly popular, but poor Wi-Fi conditions and network handovers can lead to a subpar gaming experience. We propose ODIN (On-Device Intelligence), a novel Neural Network (NN) based cross-layer QUIC gaming proxy, to address these challenges. ODIN incorporates a network quality monitoring framework that predicts Wi-Fi contention using NN, ensuring optimal network selection for gaming applications. We evaluated ODIN through live-air experiments with top-chart Android gaming apps. By leveraging the advantages of QUIC and NN, ODIN outperforms legacy smartphones, providing a better gaming experience. ODIN surpasses Multipath TCP (MPTCP) for thin-stream applications by efficiently using mobile data and delivering seamless user experiences during network handovers, demonstrated in the BrawlStars game's zero-touch and zero-lag handover mechanism. We also introduced ODIN-LITE, a lightweight approach with 25% better power consumption efficiency than MPTCP full-mesh mode. ODIN 's efficient mobile data and power use aligns with Industry 5.0 principles, fostering harmony between human-centric gaming experiences and advanced network technologies. Its application-agnostic design and zero kernel dependency facilitate wide-scale deployment, making it a promising solution for the gaming industry's future.
引用
收藏
页码：4536 / 4547
页数：12
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