PopCorns: Power Optimization Using a Cooperative Network-Server Approach for Data Centers
PopCorns: Power Optimization Using a Cooperative Network-Server Approach for Data Centers
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DOI：
10.1109/icccn.2018.8487409
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发表时间：
2018-07
期刊：
影响因子：
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通讯作者：
Bingqian Lu;Sai Santosh Dayapule;Fan Yao;Jingxin Wu;Guru Venkataramani;S. Subramaniam
中科院分区：
文献类型：
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作者：
Bingqian Lu;Sai Santosh Dayapule;Fan Yao;Jingxin Wu;Guru Venkataramani;S. Subramaniam
数据中心已成为各种应用的流行计算平台，占美国总能耗的近2%。因此，优化数据中心电源并减少其能源足迹变得非常重要。随着数据中心基础设施和冷却设备采用新的节能设计，服务器和网络等活动组件将随着新出现的工作负载消耗大部分电力。大多数现有的工作独立地优化服务器和网络中的功率，并且不以可以实现更大功率节省的整体方式一起解决它们。在本文中，我们提出了PopCorns，一个合作的服务器网络框架的功率优化。我们提出了低功耗模式的交换机和服务器的电源模型。我们还设计了作业调度算法，将任务放在服务器上的功率感知的方式，使服务器和网络交换机可以有效地利用低功耗状态。我们的实验结果表明，我们能够实现超过20%的更高的功率节省相比，在服务器上执行平衡的作业分配的基线策略。
Data centers have become a popular computing platform for various applications, and account for nearly 2% of total US energy consumption. Therefore, it has become important to optimize data center power, and reduce their energy footprint. With newer power- efficient design in data center infrastructure and cooling equipment, active components such as servers and the network consume most of the power with emerging sets of workloads. Most existing work optimizes power in servers and networks independently, and do not address them together in a holistic fashion that can achieve greater power savings. In this paper, we present PopCorns, a cooperative server-network framework for power optimization. We propose power models for switches and servers with low-power modes. We also design job scheduling algorithms that place tasks onto servers in a power-aware manner, such that servers and network switches can take effective advantage of low-power states. Our experimental results show that we are able to achieve more than 20% higher power savings compared to a baseline strategy that performs balanced job allocation across the servers.