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An algorithm for network and data-aware placement of multi-tier applications in cloud data centers

机译:云数据中心中多层应用程序的网络和数据感知放置算法

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Today's Cloud applications are dominated by composite applications comprising multiple computing and data components with strong communication correlations among them. Although Cloud providers are deploying large number of computing and storage devices to address the ever increasing demand for computing and storage resources, network resource demands are emerging as one of the key areas of performance bottleneck. This paper addresses network-aware placement of virtual components (computing and data) of multi-tier applications in data centers and formally defines the placement as an optimization problem. The simultaneous placement of Virtual Machines and data blocks aims at reducing the network overhead of the data center network infrastructure. A greedy heuristic is proposed for the on-demand application components placement that localizes network traffic in the data center interconnect. Such optimization helps reducing communication overhead in upper layer network switches that will eventually reduce the overall traffic volume across the data center. This, in turn, will help reducing packet transmission delay, increasing network performance, and minimizing the energy consumption of network components. Experimental results demonstrate performance superiority of the proposed algorithm over other approaches where it outperforms the state-of-the-art network aware application placement algorithm across all performance metrics by reducing the average network cost up to 67% and network usage at core switches up to 84%, as well as increasing the average number of application deployments up to 18%.
机译:当今的云应用程序主要由包含多个计算和数据组件的复合应用程序组成,这些组件之间具有强大的通信关联性。尽管云提供商正在部署大量计算和存储设备来满足对计算和存储资源不断增长的需求,但是网络资源需求正在成为性能瓶颈的关键领域之一。本文介绍了数据中心中多层应用程序的虚拟组件(计算和数据)的网络感知放置,并将该放置正式定义为优化问题。虚拟机和数据块的同时放置旨在减少数据中心网络基础结构的网络开销。针对按需应用程序组件的放置提出了贪婪的启发式方法,该方法将数据中心互连中的网络流量本地化。这种优化有助于减少上层网络交换机中的通信开销,从而最终减少整个数据中心的总流量。反过来,这将有助于减少数据包传输延迟,提高网络性能并最小化网络组件的能耗。实验结果表明,通过将平均网络成本降低多达67%,将核心交换机的网络使用率降低多达67%,该算法在所有性能指标上均优于最新的网络感知应用程序放置算法,其性能优于其他方法。 84%,并且将平均应用程序部署数量提高到18%。

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