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Joint Optimization of Task Placement and Routing in Minimizing Inter-DC Coflow Completion Time

机译:最小化DC COFLOW完成时间的任务放置和路由的联合优化

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With the rapidly growing of geo-distributed applications in the Internet, there is a huge amount of data generated in geo-distributed datacenters everyday. However, because of region privacy concerns and limitation of inter-DC WAN bandwidth, moving all the geo-distributed data to a single datacenter for centralized processing is not practical. Therefore, we intend to process the data where it generates by the big data applications and optimize the coflow routing in inter-DC WAN to improve the performance of the applications. Previous studies consider only routing or task placement optimization, which is inefficient. In this paper, we propose an algorithm PRO with an approximation ratio (1 + ?) that jointly optimize the placement of tasks and the routing of a coflow. Our proposed algorithm can efficiently reduce the coflow completion time.
机译:随着互联网中的迅速增长的地理分布式应用程序,每天在地理分布式数据中心产生大量数据。但是,由于区域隐私问题和DC WAN带宽的限制,将所有地理分布式数据移动到单个数据中心以进行集中处理并不实用。因此,我们打算处理由大数据应用程序生成的数据,并优化DC WAN中的CoFlow路由以提高应用程序的性能。以前的研究考虑只考虑路由或任务放置优化,这是效率低下的。在本文中,我们提出了一种具有近似比(1 +)的算法专业,该算法共同优化任务的放置和Coflow的路由。我们所提出的算法可以有效地减少COFLOW完成时间。

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