Evaluation of container-scheduling algorithms for cluster management in the public cloud
As the demand for efficient resource utilization in public cloud environments continues to rise, container scheduling algorithms play a pivotal role in optimizing the deployment and execution of applications. This study evaluates the efficacy of various container-scheduling algorithms, with a focus...
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Nanyang Technological University
2024
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sg-ntu-dr.10356-1751172024-04-26T15:40:32Z Evaluation of container-scheduling algorithms for cluster management in the public cloud Kwa, Keane Bing Hong Tang Xueyan School of Computer Science and Engineering ASXYTang@ntu.edu.sg Computer and Information Science As the demand for efficient resource utilization in public cloud environments continues to rise, container scheduling algorithms play a pivotal role in optimizing the deployment and execution of applications. This study evaluates the efficacy of various container-scheduling algorithms, with a focus on determining the Stratus algorithm's ability to outperform Google's Borg algorithm on real-world cloud workloads run on Google Cloud. Through rigorous experimentation and data analysis, we find that the Stratus algorithm outperforms Google's Borg algorithm, especially in terms of the running cost of the instances - where we observed a 72% reduction in cost. However, the Stratus algorithm does not consider some intricacies of a cluster management setup, such as task constraints and dependencies. Hence, the Stratus algorithm is a more suitable algorithm for a customer looking to setup their own scheduling algorithm on the cloud, than for the purpose of cluster management for a cloud service provider. Bachelor's degree 2024-04-22T00:49:09Z 2024-04-22T00:49:09Z 2024 Final Year Project (FYP) Kwa, K. B. H. (2024). Evaluation of container-scheduling algorithms for cluster management in the public cloud. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/175117 https://hdl.handle.net/10356/175117 en SCSE23-0328 application/pdf Nanyang Technological University |
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Computer and Information Science Kwa, Keane Bing Hong Evaluation of container-scheduling algorithms for cluster management in the public cloud |
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As the demand for efficient resource utilization in public cloud environments continues to rise, container scheduling algorithms play a pivotal role in optimizing the deployment and execution of applications. This study evaluates the efficacy of various container-scheduling algorithms, with a focus on determining the Stratus algorithm's ability to outperform Google's Borg algorithm on real-world cloud workloads run on Google Cloud. Through rigorous experimentation and data analysis, we find that the Stratus algorithm outperforms Google's Borg algorithm, especially in terms of the running cost of the instances - where we observed a 72% reduction in cost. However, the Stratus algorithm does not consider some intricacies of a cluster management setup, such as task constraints and dependencies. Hence, the Stratus algorithm is a more suitable algorithm for a customer looking to setup their own scheduling algorithm on the cloud, than for the purpose of cluster management for a cloud service provider. |
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Tang Xueyan |
author_facet |
Tang Xueyan Kwa, Keane Bing Hong |
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Final Year Project |
author |
Kwa, Keane Bing Hong |
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Kwa, Keane Bing Hong |
title |
Evaluation of container-scheduling algorithms for cluster management in the public cloud |
title_short |
Evaluation of container-scheduling algorithms for cluster management in the public cloud |
title_full |
Evaluation of container-scheduling algorithms for cluster management in the public cloud |
title_fullStr |
Evaluation of container-scheduling algorithms for cluster management in the public cloud |
title_full_unstemmed |
Evaluation of container-scheduling algorithms for cluster management in the public cloud |
title_sort |
evaluation of container-scheduling algorithms for cluster management in the public cloud |
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Nanyang Technological University |
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2024 |
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https://hdl.handle.net/10356/175117 |
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1814047334618628096 |