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Cloud computing is the very demanding technology. in current time. Cloud computing provide the all-inone solution like storage, computational machine, server, database, application in the single platform by the cloud service provider. In the cloud computing autoscaling is the most important component because availableness of the service directly depends on the scalability. The aim of this paper presents a comprehensive analysis of current state-of-the-art autoscaling algorithms using reinforcement learning techniques within cloud computing and resource management systems. In the last few years, the crossing of autoscaling and reinforcement learning has collected important attention because of its capacity to actively use its resources allocation in composed and attentive environment.
Joshi et al. (Sat,) studied this question.
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