TL;DR
An Enhanced Container Scheduler (ECSched) is proposed for efficiently scheduling concurrent container requests on heterogeneous clusters with multi-resource constraints and outperforms state-of-the-art container schedulers in container performance and resource efficiency.
The DQN-Scheduler is introduced, a novel reinforcement learning-based agent designed to optimize microservice scheduling in cloud environments and is believed to be the first framework to address all these objectives simultaneously.
The results suggest that process-level orchestration combined with automated monitoring components can serve as a practical alternative for hosting small Express.js services.
This paper analyzes the main influencing factors related to the formation mechanism and optimization path of cold starts, focusing on code download, instance startup, runtime initialization, and user code initialization, and summarizes methods such as container reuse, snapshot recovery, warm-up and elastic scaling, int...
A random forest enhanced particle swarm optimization algorithm (RFPSO) is proposed, which implements intelligent initialization of resource allocation through a random forest model, which improves the efficiency of finding optimal solutions and ensures that critical tasks can prioritize access to higher-performance com...
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