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The load balancing based on the estimated finish time of tasks in cloud computing

机译:基于估计的云计算任务完成时间的负载平衡

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The performance parameters are parameters with which we measure and test the profitability and the performances of several static or dynamic load balancing algorithms. The static load balancing algorithms, share the client query between virtual machines in a data center for the processing. But, there is a problem when it comes to the current load of each virtual machine. The dynamic algorithms as "Efficient Response Time Load Balancer" and "Mini time processing load balancer" prove to be a solution to respond to this problem The advantage of these algorithms, before allocating a task, is that they search in the allocation tables on the virtual machine, with a metric which is quite inferior (be it the response time or the processing time). In this paper, we propose a new improvement of the load balancing by the algorithm "estimated finish time load balancer", that takes into account, the current load of the virtual machine of a data center and the estimation of the processing finish time of a task before any allocation, in order to overcome the problems caused by the static algorithms. The algorithm "estimated finish time load balancer" allows cloud service providers, to improve the performance, availability and maximize the use of virtual machines in their data centers.
机译:性能参数是用于衡量和测试几种静态或动态负载平衡算法的盈利能力和性能的参数。静态负载平衡算法在数据中心的虚拟机之间共享客户端查询以进行处理。但是,每个虚拟机的当前负载都存在问题。动态算法“有效响应时间负载均衡器”和“最小时间处理负载均衡器”被证明是解决此问题的解决方案。这些算法的优点是,在分配任务之前,它们会在分配表上进行搜索。虚拟机,其度量标准很差(响应时间或处理时间)。在本文中,我们提出了一种通过“估计完成时间负载均衡器”算法对负载均衡进行的新改进,该算法考虑了数据中心虚拟机的当前负载以及对数据中心虚拟机处理结束时间的估计。任务分配之前,以克服静态算法所引起的问题。该算法“估计完成时间负载平衡器”使云服务提供商可以提高性能,可用性并最大程度地在其数据中心使用虚拟机。

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