Machine learning & Deep learning based Load Balancing Algorithms techniques in Cloud Computing

Ronak Agarwal, D. Sharma
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引用次数: 3

Abstract

Cloud computing is a fledgling technology that provides computers in terms of efficient resource efficiency. The advancement of new applications in the cloud brings on an increase in load on servers. In addition to the many studies conducted in the province of Cloud computing, it still has to face some provocations, such as load balancing(LB) that require further upgrades and models for better performance and to achieve maximum user satisfaction. In this paper, we have discussed about the Machine Learning Techniques used to build VM teams according to their CPU. Deep Learning (DL) techniques are used to achieve QoS which implies improving of resource utilization and deployment; while reducing delays, response time and costs, balancing the load on all equipment, therefore, increases system reliability. This paper contains a comprehensive overview of a few machine learning as well as deep learning based algorithm on load balancing.
云计算中基于机器学习和深度学习的负载平衡算法技术
云计算是一种新兴的技术,它为计算机提供了高效的资源效率。云中的新应用程序的发展带来了服务器负载的增加。除了在云计算领域进行的许多研究之外,它还必须面对一些挑战,例如负载平衡(LB),需要进一步升级和模型,以获得更好的性能和最大的用户满意度。在本文中,我们讨论了用于根据CPU构建VM团队的机器学习技术。深度学习(DL)技术用于实现QoS,这意味着提高资源的利用率和部署;在减少延迟、响应时间和成本的同时,平衡所有设备的负载,从而提高了系统的可靠性。本文全面概述了几种基于机器学习和深度学习的负载平衡算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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