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Adaptive Scheduling Algorithm Based Task Loading in Cloud Data Centers
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DOI：10.1109/ACCESS.2022.3168288.png)
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Abstract
En 中文
Cloud computing is a global storage framework whereby users use the tools, including the computation, storage, network, etc., that are provided automatically. The computational has led the cloud data centers to be stored in digital services that many consumers distribute. The biggest problem with cloud data centers is handling the millions of users' continuous proposals. Therefore, in this paper, Adaptive Scheduling Algorithm Based Task Loading (ASA-TL) has been proposed to manage cloud data centers' task to be stored in digital devices. ASA is implemented in which the task is shared between all the current virtual servers,and the cloud data are protected from overloading. The data assignment is made by taking account of the importance and status of the digital device that helps to assign task fairly and use them efficiently. TL manages these requests efficiently, and the task input must be equally and reliably allocated between various processors. The experimental result suggests that ASA-TL achieves the highest performance assessment measurements, including response time, processing time in the data center and overall expense.
Keywords:
Cloud computing
Task analysis
Resource management
Data centers
Servers
Loading
Load management
Data center
cloud computing
response time
task management
Journal
IF:
3.6
Papers:
9.8W
Citations:
29.4W
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