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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：考虑到云计算的使用不断增长以及对云中资源的最佳利用的需求，并关注基于按使用量付费的基础付费用户使用服务的用户，应该为用户提供一种更快捷的方法减少用户的等待时间和任务的等待时间。本文的主要目的是利用两种传统的Min-Min和Max-Min算法的优势提供一种最优算法。此算法（TOMMP）中的另一点是任务的优先级。当今世界上有很多调度算法，但是在大多数算法中，任务的优先级已被忽略和忽略。在该算法中，首先基于优先级算法为任务选择优先级，然后使用中位数确定要使用Min-Min或Max-Min算法中的哪一种。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，并且被证明比可比算法更好。

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