CoCG: Fine-grained Cloud Game Co-location on Heterogeneous Platform

Cloud games have received widespread attention and exponential growth recently as a key technology for building metaverse. Unlike general tasks in the cloud, the scene-complex, latency-critical, and interaction-intensive features make it challenging for cloud game co-deployment on heterogeneous platforms. Game-grained resource allocation leads to low resource effectiveness. Although previous work tries to explore individual game partitioning methods, they still face the problem of inefficient game hosting decisions and ultimately QoS violations. In this paper, we propose a fine-grained game characteristic and scheduling strategy to co-locate games together for high resource usage effectiveness. First, we fully explore the relationships between game scenes and resource usage behaviors by breaking the cloud game into stages with multiple frames and clustering them. We adopt machine learning methods to predict game resource consumption in real-time. To further improve multi-game parallelism, we co-locate games in a complementary way and steal time from the loading stage to avoid oversubscribing. The evaluation shows that our work increased the throughput of the cloud game deployments by 23.7% with low overhead compared to previous work.