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Load balancing job assignment for cluster-based cloud computing

机译:基于集群的云计算的负载均衡作业分配

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The load balancing problem is one of an open issues for the cloud computing. A good load balancing mechanism enhances the performance of network processing, optimizes the use of resources, and ensures that no overloading a single node or link case. The existing load balancing cloud computing research mainly unilateral the fairness of the transmission network or stand only for the system. Hence, this work considers the handling of both network and system load balancing to obtain high performance. To assign the tasks to the same type of nodes along the links with minimum processing and transmission delays subject to the capacities of nodes and links. Three task assignment schemes FCFS, Min-Min, and Min-Max are adopted along with dynamic clustering, which is a method to group the same type of cloud servers. This study changes in the variables manipulated with the number of nodes and the number of tasks and records the maximal end-to-end delay, average end-to-end delay and fairness index, to analyze the load balancing results. The results show that the Min-Max combination with dynamic clustering has a good effect.
机译:负载平衡问题是云计算的未解决问题之一。良好的负载平衡机制可以提高网络处理的性能,优化资源的使用,并确保单个节点或链路情况不会过载。现有的负载均衡云计算研究主要是单方面的传输网络的公平性或仅代表系统。因此,这项工作考虑了网络和系统负载平衡的处理以获得高性能。根据节点和链接的容量,以最小的处理和传输延迟将任务分配给链接上的相同类型的节点。动态聚类采用了三种任务分配方案FCFS,Min-Min和Min-Max,这是对相同类型的云服务器进行分组的一种方法。本研究通过节点数和任务数来控制变量的变化,并记录最大端到端延迟,平均端到端延迟和公平性指标,以分析负载均衡结果。结果表明,最小-最大结合动态聚类具有良好的效果。

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