Abstract
With the rise of online applications such as machine learning, stream processing, and interactive data-intensive applications in shared clusters, container cluster scheduling in data centers is facing new challenges. In order to solve the problem that application performance and economic cost cannot be balanced in a container cluster deploying a hybrid application, this paper proposes a container cluster scheduling strategy based on delay decision under multi-dimensional constraints. Formal language-based application placement constraints were introduced, and a task reorder model was established based on delayed decision-making. The experiments show that this strategy improves application performance and cluster utilization.
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