2021
DOI: 10.1007/s42979-021-00730-5
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A Novel Feature Extraction Model for Large-Scale Workload Prediction in Cloud Environment

Abstract: In an enterprise cloud environment, it is difficult to handle an extensive number of loads. Serving the request in very less time leads to resource allocation problem. It is better to have prior knowledge of the incoming loads to auto-scale the resources. A novel architecture is proposed for the better prediction of workloads in the cloud environment. The proposed feature extraction model considers three essentials for managing cloud resources, i.e., CPU, Disk, and Memory. The model with the very nominal error… Show more

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Cited by 5 publications
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“…To address issues pertaining to the performance of task scheduling [3][4][5], researchers have presented a variety of innovative approaches. The following categories generally describe the available task-scheduling techniques in a cloud environment.…”
Section: Introductionmentioning
confidence: 99%
“…To address issues pertaining to the performance of task scheduling [3][4][5], researchers have presented a variety of innovative approaches. The following categories generally describe the available task-scheduling techniques in a cloud environment.…”
Section: Introductionmentioning
confidence: 99%