云计算中任务调度的IDEA、BATS、ARIMA和排队模型的实现

M. B. Gawali, S. Shinde
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引用次数: 4

摘要

在当今的技术时代,云计算是最受欢迎的,因为它的动态性质,根据用户的需要或请求提供资源。按服务付费的定价模式为云计算增添了最强大的优势。这些服务可以随时随地获得和使用,这使得云计算更加流行。但是云计算仍然面临着许多问题。任务调度和资源分配就是其中之一。实际上,这些是影响这项技术的独立问题。最优的任务调度和有效的资源分配为云服务提供商在QoS(服务质量)方面提供了最大的好处。本文是在基于排队休假的任务完成算法、IDEA、BATS、ARIMA和节能算法中,找出所需完成时间较少的任务完成算法的初步实验工作。本文通过实验证明,对于Berger模型的输入数据,BATS算法是较好的任务完成时间算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Implementation of IDEA, BATS, ARIMA and queuing model for task scheduling in cloud computing
In today's technological era, the cloud computing is the most popular because of its dynamic nature to provide the resources as per the user's need or request. The pay as per service pricing model add the strongest corner into the cloud computing. The services can be available and used anywhere, anytime makes the cloud computing more popular. But still the cloud computing has facing many issues. Task scheduling and resource allocation is one of them. Actually, these are separate issues which affected on this technology. The optimum scheduling of task with efficient allocation of resources have provide the maximum benefits to the cloud service provider in terms of QoS(Quality of Service). This is the preliminary experimental work to identify the less finish time require task completion algorithm out of, IDEA, BATS, ARIMA and Energy-saving based on queuing vacation. This paper has experimentally proves the BATS is better algorithm for task completion time with respect to the Berger Model input data.
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