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Optimization of tasks in cloud computing based on MAX-MIN, MIN-MIN and priority

机译:基于MAX-MIN,MIN-MIN和优先级的云计算中的任务优化

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Considering the growing use of cloud computing and the need for optimal use of resources in the cloud, and attention to users that pay for services they use based on their pay-as-you-go basis, There should be a quicker way for users to decrease the user's waiting time and task's waiting time. The main purpose of this paper is to provide an optimal algorithm using the advantages of the two traditional Min-Min and Max-Min algorithms. The other point that follow in this algorithm (TOMMP) is the priority of the tasks. There are a lot of scheduling algorithms in the world today, but the priority given to the tasks has been neglected and overlooked in most algorithms. In this algorithm, priority is firstly selected for tasks based on a prioritization algorithm, and then using the median number to decide which one of the Min-Min or Max-Min algorithms is to be used. It should be noted that according to the TOMMP algorithms, its waiting time is lower than comparisons of the compared algorithms and is shown to be better than the comparable algorithms.
机译:考虑到云计算的越来越多的使用以及对云中资源的最佳利用的需求,并关注支付他们使用的服务支付的用户,这些用户基于您的付费基础,应该有更快的方式减少用户的等待时间和任务的等待时间。本文的主要目的是使用两个传统的MIN-MIN和MAX-MIN算法的优点提供最佳算法。在该算法(Tommp)中遵循的另一个点是任务的优先级。今天世界上有很多调度算法,但在大多数算法中忽略并忽略了任务的优先级。在该算法中,首先基于优先级算法选择优先级,然后使用中值号码来确定要使用哪一个min-min或max-min算法。应该注意的是,根据Tommp算法,其等待时间低于比较算法的比较,并且被示出比可比较的算法更好。

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