...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Journal of ambient intelligence and humanized computing >An optimal big data processing for smart grid based on hybrid MDM/R architecture to strengthening RE Integration and EE in datacenter
【24h】

An optimal big data processing for smart grid based on hybrid MDM/R architecture to strengthening RE Integration and EE in datacenter

机译：基于混合MDM / R架构的智能电网最佳大数据处理，以增强数据中心的RE集成和EE

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Supply chain is a hard business area, where you need to have a perfect balance between demand and supply, day in and day out, by an intricate system that sits underneath it all. Achieving such a system by meeting the ambitious targets of the agreement on climate change can only be achieved through an effective combination of energy efficiency and renewable energy integration. The uncertainty and variability of renewable energy generation can pose challenges for grid operators and can requires additional actions to balance the system. Significant researches which aim is to improve energy efficiency of data center indicates that operating reserves could be procured from many complex and costly techniques. In this paper, we investigate the problem from scheduling of workloads in a data center in order to minimize its energy consumption budget, minimize the conventional grid dependence, and maximize the renewable energy provided to data center, by the ability to temporarily delay or degrade service, with a modified supply-following algorithm. This algorithm attempts to align power consumption with the amount of wind power available, while minimizing the time by which jobs exceed their deadlines. Modification of the algorithm has been performed in the direction of big data processing (wind trace, workload requests, prices, horizontal ellipsis ), servers management. This modification is performed by jobs classification into predefined classes using the classification and regression trees algorithm. New hybrid architecture that manages the Meter Data Management Repository MDM/R was introduced using MapReduce programming model for ETL process and Massive Parallel Processing Database for requests which strongly influences the accuracy and the speediness of the scheduler.
机译：供应链是一个艰苦的业务领域，您需要通过位于其下方的错综复杂的系统，在日常需求中实现供需之间的完美平衡。通过实现气候变化协议中雄心勃勃的目标来实现这样的系统，只有通过有效结合能源效率和可再生能源，才能实现。可再生能源发电的不确定性和可变性可能给电网运营商带来挑战，并可能需要采取其他措施来平衡系统。旨在提高数据中心能源效率的大量研究表明，可以从许多复杂且昂贵的技术中获取运营储备。在本文中，我们通过临时延迟或降级服务的能力来调查数据中心中的工作负载调度问题，以最大程度地减少其能源消耗预算，最小化传统的网格依赖性以及最大化提供给数据中心的可再生能源。 ，具有改进的供应跟踪算法。该算法尝试使功耗与可用的风力功率保持一致，同时最大程度地减少作业超出其截止日期的时间。已经在大数据处理（风向跟踪，工作量请求，价格，水平省略号），服务器管理的方向上对算法进行了修改。通过使用分类和回归树算法将作业分类到预定义的类别中，可以执行此修改。引入了用于管理电表数据管理存储库MDM / R的新混合体系结构，该体系结构使用ETL过程的MapReduce编程模型和大规模并行处理数据库来处理对请求的影响，这些请求极大地影响了调度程序的准确性和速度。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号