CSR: Small: Understanding and Modeling the Trade-Offs in Data Centers for Next-Generation Sustainable Management

云计算作为一种商业模式的成功已经导致了几种用于存储、数据挖掘和搜索以及多媒体内容交付的商业云服务。随着云服务渗透新兴市场 --特别是智能手机市场--传统的公用事业服务，如电视正在成为？多云。？ 随着经济越来越依赖云数据中心（DC）的高效运营，对设计的需求越来越迫切？绿色？和能源自适应管理软件，可在不同的工作负载和能源条件下优化地理上分布的数据中心组的操作。网络物理、主动和预测性决策对于DC操作系统至关重要，在同一服务器上运行多个作业时的工作负载和功耗，并做出决策，例如，用于在不同数量的可用DC、电力成本、可再生能源供应的百分比和能量存储容量之间重新分配服务虚拟机。该项目正在解决由于一系列复杂因素而产生的DC管理决策所涉及的科学和工程挑战-例如，服务器异质性、DC与其环境之间的网络物理交互、变化的工作负载和电价-以及权衡-例如，能量延迟、时间精度和冷却计算。该项目正在开发一个绿色网络物理数据中心模拟器GDCSim，用于研究在实际情况下的权衡与几个复杂的因素。 该项目旨在实现更可持续的云计算，并为绿色经济培养工程师。 该项目的研究结果是通过亚利桑那州立大学的影响实验室？的网站（http：//impact.asu.edu/）。

The success of cloud computing as a business model has led to several commercial cloud services for storage, data mining and searching, and multimedia content delivery. As cloud services penetrate emerging markets -- notably the smart-phone market -- conventional utility services such as television are becoming ?cloudized.? As the economy becomes more dependent on the efficient operation of cloud data centers (DCs), there?s an increasingly urgent need to design ?green? and energy-adaptive management software that optimizes the operation of a geographically distributed set of data centers under varying workload and energy conditions.Cyber-physical, proactive and predictive decision making is essential for a DC operating system that efficiently predicts, e.g., the workload and the power consumption when running multiple jobs on the same server and makes decisions, e.g., for redistributing the servicing virtual machines among varying number of available DCs, electricity cost, percentage of renewable energy supply and capacity of energy storage. This project is addressing the scientific and engineering challenges involved in decision making of such DC management arising from an array of complicating factors -- e.g., server heterogeneity, cyber-physical interactions between DCs and their environment, varying workload and electricity pricing -- and trade-offs -- e.g., energy-delay, time-accuracy, and cooling-computing . The project is developing a Green cyber-physical Data Center Simulator, GDCSim, for studying the tradeoffs in practical scenarios with several complicating factors. Project aims to enable a more sustainable cloud computing and to train engineers for a greener economy. The project findings are available through ASU-IMPACT lab?s website (http://impact.asu.edu/).