Latency Reduction and Input Prediction for Cloud Gaming Clients
subject: browser-based; clientside; cloud gaming; input prediction; latency; real-time systems
description: Cloud gaming enables access to high-quality games on thin clients by streaming rendered content from remote servers, but network-induced latency remains a critical barrier to responsive gameplay. This paper presents a browser-based system that profiles user input in real-time, employs a lightweight machine learning model to predict actions, and dynamically compensates for lag by speculative input. Our solution reduces perceived lag by up to 25% and maintains a 94%+ prediction accuracy, fully within a free-tier cloud environment. Compared to traditional infrastructure-based approaches, our method imposes no proprietary hardware requirements and offers platform-wide scalability. 2025 IEEE.
creator: Payankan, Gavin George; Singal, Neha; Saxena, Surabhi
source: Proceedings - 2025 International Conference on Transformative Computing Technologies, ICTCT 2025;pp.30-34
publisher: Institute of Electrical and Electronics Engineers Inc.
date: 01-01-2025
rights: Restricted Access; Hardcopy may be available in the library
relation: ISBN: 979-833159195-3;
language: English
type: Conference paper
coverage: Payankan G.G., Christ University, Dept. of Computer Science, Bengaluru, India; Singal N., Christ University, Dept. of Computer Science, Bengaluru, India; Saxena S., Christ University, Dept. of Computer Science, Bengaluru, India