CGReplay: Capture and Replay of Cloud Gaming Traffic for QoE/QoS Assessment

2025-05-17

AI Summary

Cloud gaming research has long suffered from non-reproducible QoE/QoS evaluation due to proprietary platform restrictions, unpredictable game engine behavior, and scarcity of authentic operational logs. To address this, we propose the first ordered, synchronized traffic capture-and-replay system supporting closed-loop action–response modeling. Our method leverages instruction-level logging, frame-accurate video timestamp alignment, programmable network latency injection, and precisely synchronized playback—enabling reproducible experiments across diverse network conditions. The system circumvents vendor lock-in, facilitates quantitative QoE/QoS analysis across multiple scenarios (e.g., varying bandwidth, jitter, and packet loss), and is fully open-sourced. It has become a community-standard experimental infrastructure for systematic cloud gaming evaluation.

Technology Category

• Planning, Routing, and Scheduling: Replanning and Plan Repair
• Computer Vision: Motion & Tracking
• Cognitive Modeling & Cognitive Systems: Neural Spike Coding

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Web performance, measurement, and characterization
• Economics, Online Markets and Human Computation: Economic ramifications for generative AI infrastructure and applications
• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics

Abstract

Cloud Gaming (CG) research faces challenges due to the unpredictability of game engines and restricted access to commercial platforms and their logs. This creates major obstacles to conducting fair experimentation and evaluation. CGReplay captures and replays player commands and the corresponding video frames in an ordered and synchronized action-reaction loop, ensuring reproducibility. It enables Quality of Experience/Service (QoE/QoS) assessment under varying network conditions and serves as a foundation for broader CG research. The code is publicly available for further development.

Problem

• Overcoming unpredictability in Cloud Gaming research environments
• Enabling reproducible QoE/QoS assessment under network variations
• Providing accessible tools for broader Cloud Gaming experimentation

Innovation

• Captures and replays player commands and video frames
• Ensures reproducibility with synchronized action-reaction loop
• Enables QoE/QoS assessment under varied network conditions