Stimpack: An Adaptive Rendering Optimization System for Scalable Cloud Gaming

TL;DR

Stimpack is an adaptive system that optimizes cloud gaming rendering quality by balancing resource costs and user experience, significantly improving efficiency and user satisfaction.

Contribution

It introduces a novel adaptive optimization approach for cloud gaming that considers lossy network effects and resource efficiency, with an open-source implementation.

Findings

Stimpack achieves up to 24% higher service quality.

It can serve twice as many users with the same resources.

User study confirms improved user experience.

Abstract

In distributed multimedia applications, content is often delivered to users in a degraded form due to network-induced lossy compression. Real-time and interactive use cases like cloud gaming, which render content on the fly, require low latency and are hosted at resource-constrained edge servers. We present a new insight: when rendered content is delivered over a network with lossy compression, high-quality rendering can be ineffective in improving user-perceived quality, leading to a poor return on computing resources. Leveraging this observation, we built Stimpack, a novel system that adaptively optimizes game rendering quality by balancing server-side rendering costs against user-perceived quality. The system uses a mechanism that quantifies the efficiency of resource usage to maximize overall system utility in multi-user scenarios. Our open-sourced implementation and extensive evaluations show that Stimpack achieves up to 24% higher service quality and serves twice as many users with the same resources compared to baselines. A user study further validates that Stimpack provides a measurably better user experience.