Abstract
This paper presents new multi-objectives scheduling strategies implemented in Docker SwarmKit. Docker SwarmKit is a container toolkit for orchestrating distributed systems at any scale. Currently, Docker SwarmKit has one scheduling strategy called Spread. Spread is based only on one objective to select from a set of cloud nodes, one node to execute a container. However, the containers submitted by users to be scheduled in Docker SwarmKit are configured according to multi-objectives criteria, as the number of CPUs and the memory size. To better address the multi-objectives configuration problem of containers, we introduce the concept and the implementation of new multi-objectives scheduling strategies adapted for Cloud Computing environments and implemented in Docker SwarmKit. The principle of our multi-objectives strategies consist to select a node which has a good compromise between multi-objectives criteria to execute a container. The proposed scheduling strategies are based on a combinaison of PROMETHEE and Kung multi-objectives decision algorithms in order to place containers. The implementation in Docker SwarmKit and experiments of our new strategies demonstrate the potential of our approach under different scenarios.
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Acknowledgments
This work is funded by the French Fonds Unique Ministériel (FUI) Wolphin Project. We thank Grid5000 team for their help to use the testbed.
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Menouer, T., Cérin, C., Leclercq, É. (2018). New Multi-objectives Scheduling Strategies in Docker SwarmKit. In: Vaidya, J., Li, J. (eds) Algorithms and Architectures for Parallel Processing. ICA3PP 2018. Lecture Notes in Computer Science(), vol 11336. Springer, Cham. https://doi.org/10.1007/978-3-030-05057-3_8
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DOI: https://doi.org/10.1007/978-3-030-05057-3_8
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