Abstract
As a new type of computing resource, cloud computing attracts more and more users because it is convenient and quick service. The cloud server is used by a large number of users, which brings about the problem of how to reasonably schedule resources to ensure the load balance of the cloud environment. With the development of research, scholars have found that the simple job scheduling of physical resources cannot meet the utilization of resources. Connecting the characteristic of resource scheduling in cloud environment and machine learning, researchers gradually abstract a resource scheduling problem into a mathematical problem, and then combine machine learning with group algorithm to put forward the intelligent algorithm which can optimize the resource structure and the improve the resource utilization. In this survey, we discuss several algorithms that use machine learning to solve resource scheduling problems in a cloud environment. Experiments show that machine learning can assist the cloud environment to achieve load balancing.
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Acknowledgements
This work is supported by Marie Curie Fellowship (701697-CAR-MSCA-IF-EF- ST), the NSFC (61300238 and 61672295), the 2014 Project of six personnel in Jiangsu Province under Grant No. 2014-WLW-013, and the PAPD fund.
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Liu, Q., Jiang, Y. (2018). A Survey of Machine Learning-Based Resource Scheduling Algorithms in Cloud Computing Environment. In: Sun, X., Pan, Z., Bertino, E. (eds) Cloud Computing and Security. ICCCS 2018. Lecture Notes in Computer Science(), vol 11063. Springer, Cham. https://doi.org/10.1007/978-3-030-00006-6_21
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