首页> 外文期刊>EURASIP journal on embedded systems >Energy consumption optimization management mechanism based on drug green crowd data in biological pharmaceutical cloud environment
【24h】

Energy consumption optimization management mechanism based on drug green crowd data in biological pharmaceutical cloud environment

机译:生物制药云环境中基于药物绿色人群数据的能耗优化管理机制

获取原文
           

摘要

For satisfying the network trend and intelligent demand of biopharmaceutical, we proposed the energy optimization consumption and management scheme of the drug green crowd data in the biological pharmaceutical cloud environment. First, the biopharmaceutical process are mapped to the cloud platform, which can not only adapt to the revolutionary changes in the way of biopharmaceutical research and but also build a network management platform for pharmaceutical research and development. Secondly, based on the green crowd, we reconstruct the organization structure of the cloud platform, production process, and value chain-driven portfolio, etc. Then, we divide the core of the cloud platform architecture into five substages. The green screening, reorganization, and crowd data processing will be completed by the cooperation of these stages. Finally, the drug green crowd architecture is embedded into the time domain conversion interface and the state transition interface. In addition, the state energy consumption model of the biological pharmaceutical cloud platform is constructed. The experimental results show that compared with the traditional task-driven energy consumption management mechanism, the proposed management mechanism can ensure higher throughput, higher effective flow rate, and higher effective energy consumption ratio.
机译:为满足生物制药的网络趋势和智能需求,提出了生物制药云环境下药物绿色人群数据的能源优化消耗和管理方案。首先,将生物制药过程映射到云平台,该平台不仅可以适应生物制药研究方式的革命性变化,而且可以构建用于药物研发的网络管理平台。其次,在绿色人群的基础上,我们重构了云平台的组织结构,生产流程以及价值链驱动的产品组合等。然后,我们将云平台架构的核心分为五个子阶段。这些阶段的合作将完成绿色筛选,重组和人群数据处理。最后,药物绿色人群体系结构被嵌入到时域转换接口和状态转换接口中。另外,构建了生物制药云平台的状态能耗模型。实验结果表明,与传统的任务驱动型能耗管理机制相比,该管理机制能够保证更高的吞吐量,更高的有效流量和更高的有效能耗比。

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