Latency-Aware Resource Management Strategies for Real-Time Cloud Gaming Platforms
Keywords:
Cloud Gaming, Latency, Resource Management, Edge Computing, QoS Prediction, Real-Time SystemsAbstract
Cloud gaming has emerged as a transformative paradigm in the gaming industry by offloading computational workloads from end-user devices to powerful cloud servers. However, maintaining real-time responsiveness under fluctuating network conditions remains a major challenge, especially for latency-sensitive games. This paper presents a comprehensive analysis of latency-aware resource management strategies that adaptively allocate computational and network resources to ensure low latency and high-quality user experiences. Building upon recent advancements in edge computing, predictive analytics, and adaptive bitrate streaming, we propose a hybrid resource management framework that leverages predictive QoS estimation and real-time resource scaling. Through experimental simulations and architectural modeling, we demonstrate significant latency reductions and system efficiency gains, offering a scalable approach for future real-time cloud gaming platforms.
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