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Two-Aggregator Topology Optimization Using Multiple Paths in Data Center Networks

机译:使用数据中心网络中的多路径的双聚合器拓扑优化

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In this paper we focus on the problem of data aggregation using two aggregators in a data center network, where the source racks are allowed to split their data and send to the aggregators using multiple paths. We show that the problem of finding a topology that minimizes aggregation time is NP-hard for k = 2, 3, 4, where k is the maximum degree of each ToR switch (number of uplinks in a top-of-rack switch) in the data center. We also show that the problem becomes solvable in polynomial time for k = 5 and 6 and conjecture the same for k $$ 6. Experimental results show that, for k = 6, our topology optimization algorithm reduces the aggregation time by as much as 83.32 percent and reduces total network traffic by as much as 99.5 percent relative to the torus heuristic, proposed in [1] , which readily proves the significant improvement in performance achieved by the proposed algorithm.
机译:在本文中,我们专注于数据中心网络中的两个聚合器的数据聚合问题,其中允许源机架拆分其数据并使用多个路径发送到聚合器。我们表明,找到最小化聚合时间的拓扑的问题是k = 2,3,4的np - 硬,其中k是每个TOR开关的最大程度(顶部机架开关中的上行链路的数量)数据中心。我们还表明,问题在K = 5和6的多项式时间中可以在k = 5和6的猜测中变为k $ 6.实验结果表明,对于k = 6,我们的拓扑优化算法将聚集时间减少多达83.32百分比并将总网络流量减少多达99.5%,如[1]中提出的Torus启发式,这很容易证明通过所提出的算法实现的性能的显着提高。

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