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Load balancing job assignment for cluster-based cloud computing

机译:负载基于群集的云计算的均衡作业分配

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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开放问题之一。良好的负载平衡机制增强了网络处理的性能,优化了资源的使用,并确保没有重载单个节点或链接情况。现有负载平衡云计算研究主要是单方面传输网络的公平性,或仅适用于系统。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。将任务沿着具有最小处理和传输延迟的链路分配给相同类型的节点,而传输延迟受节点和链路的容量。三个任务分配方案FCFS,MIN-MIN和MIN-MAX与动态群集一起采用,这是一个用于分组相同类型的云服务器的方法。本研究在随着节点数量和任务数量的变量中的变化,并记录了最大端到端延迟,平均端到端延迟和公平性指数,分析了负载平衡结果。结果表明,MIN-MAX与动态聚类的组合具有良好的效果。

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