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Workload Optimization and Energy Consumption Reduction Strategy of Private Cloud in Manufacturing Industry

机译:制造业私有云的工作量优化与节能战略

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The private cloud of manufacturing industry whose business forms are rich and business chains long has numerous legacy systems. According to the analysis of the historical monitoring data of a private cloud system in manufacturing industry and interviews with people concerned, it is found in this paper that the private cloud in manufacturing industry could not only cope with the problems of limited capacity but also the issues of low resource utilization and excessive energy consumption in data centers caused by resource provisioning modes and characteristics of user psychology and behavior. Based on the creation of configuration management database (CMDB) and monitoring system, and combined with the features of private cloud resources provisioning, the paper tried to propose different strategies to optimize the private cloud for the platform administrator and resource users. Moreover, through optimization, sound economic and social values, such as workload improvement, energy consumption reduction, and longer expansion cycle for the private cloud platform, could be obtained.
机译:制造业的私有云,其业务形式丰富且业务链很长,具有众多的遗留系统。通过对制造业中私有云系统的历史监控数据进行分析并与相关人士进行访谈,发现制造业中的私有云不仅可以解决容量有限的问题,而且可以解决这些问题。资源调配模式以及用户心理和行为特征引起的数据中心资源利用率低和能耗过高的问题。在建立配置管理数据库(CMDB)和监控系统的基础上,结合私有云资源配置的特点,试图为平台管理员和资源用户提出不同的策略来优化私有云。此外,通过优化,可以获得良好的经济和社会价值,例如工作负载的改善,能耗的减少以及私有云平台的更长的扩展周期。

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