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- W4387251005 abstract "Scheduling tens of thousands of containers in large scale cloud-native clusters faces great challenges. Imbalanced resource utilization and fragmentation is a key challenge. To address this, we propose an efficient resource scheduling optimization method for large-scale data center. By exploiting the similarities in resource usage among instances within each cloud-native application, our approach aims to find a set of optimal application colocation hints for each application under different types of physical machines. The optimized colocation hints can be used in bin packing algorithms, allowing for efficient and effective resource management in data centers. Experiment results show that our proposed solution outperforms the classic FFD and DP algorithms in ter ms of the number of saved physical machines and the resource usage standard deviations of cluster nodes." @default.
- W4387251005 created "2023-10-03" @default.
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- W4387251005 date "2023-08-12" @default.
- W4387251005 modified "2023-10-06" @default.
- W4387251005 title "An efficient container bin-packing method for large scale cloud-native clusters" @default.
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- W4387251005 doi "https://doi.org/10.1109/ccis59572.2023.10262939" @default.
- W4387251005 hasPublicationYear "2023" @default.
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