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METHOD AND SYSTEM OF INTELLECTUAL MANAGEMENT OF RESOURCE ALLOCATION IN CLOUD COMPUTER MEDIA

机译:云计算介质中资源分配的智能管​​理方法和系统

摘要

1. A method of managing the distribution of information resources, which consists in the fact that a computer generates a model for the use and redistribution of resources, characterized in that the model for the use and redistribution of resources in cloud computing environments (Cloud computing environment) is formed in the form of a cloud IaaS (Infrastructure as a Service) models using the concept of intelligent algorithms, sequentially performing a set of operations that includes three main stages: at the first at the stage in VO, resources are allocated to the launched instance, at the second stage, the dynamic parameters of the functioning of the hosts (servers) of VO are forecasted, at the third stage, the resources are dynamically redistributed between the VO instances, and the model is formed to maximize the VO functioning efficiency indicator in accordance with expression (1) and taking into account the constraints (2): where E is a comprehensive indicator of the effectiveness of HE, reflecting the total synergistic efficiency of the execution of copies within each type of res courses VO; E, E, E, E - a set of private indicators equal to the number of copies with a satisfied need for resources, respectively, of a central processor (CPU), random access memory (RAM), disk (D) resources, network (C) resources ; T is the operating time of the HE (processor time); R is the total volume of HE resources used by the instances; R is the total amount of available HE resources, and at the first stage of the formation of the IaaS model, the best adequate host is selected for placing the instance in the HE based on the analysis of hierarchies, in the second stage, the forecast d
机译:1.一种管理信息资源的分配的方法,其特征在于,计算机生成用于资源的使用和重新分配的模型,其特征在于,该模型用于在云计算环境中使用和重新分配资源(云计算)。使用智能算法的概念以云IaaS(基础架构即服务)模型的形式形成环境,依次执行一组包括三个主要阶段的操作:在VO的第一个阶段,将资源分配给在启动的实例中,在第二阶段,预测VO的主机(服务器)功能的动态参数,在第三阶段,在VO实例之间动态重新分配资源,并形成模型以最大化VO根据表达式(1)并考虑到约束条件(2)的运行效率指标:其中,E是效果指标的综合指标HE,反映了在每种资源课程VO中执行副本的总协同效率; E,E,E,E-一组专用指示器,分别等于满足中央处理器(CPU),随机存取存储器(RAM),磁盘(D)资源,网络资源需求的副本数(三)资源; T是HE的运行时间(处理器时间); R是实例使用的HE资源的总量; R是可用HE资源的总量,在IaaS模型形成的第一阶段,根据层次结构分析,选择最佳的适当主机将实例放置在HE中,在第二阶段,将预测d

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