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Research on the selection method of multi-VM resource adjustment strategy in a single PM based on genetic algorithm

机译:基于遗传算法的单机多VM资源调整策略选择方法研究

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The selection method of resource adjustment strategy is a key step of multi-VM (Virtual Machine) resource adjustment in a single physical machine (PM). The traditional genetic algorithm (GA) do not evaluate and filter the initial population, and not make full use of decision of historical data as to increase the optimal solution time either. Based on the conventional research, this paper establishes the relation model between the service performance and the amount of resources consumption (P-R model), which is used to evaluate and filter the initial population, and presents design method of the revenue function and the termination conditions. It also presents the way which turns the empirical data into historical decision and uses it in the next cycle. The experiment results indicate the method is able to maintain high resource utilization and meets the demands of response time. (C) 2016 Published by Elsevier B.V.
机译:资源调整策略的选择方法是单个物理机(PM)中多VM(虚拟机)资源调整的关键步骤。传统的遗传算法(GA)不能对初始种群进行评估和过滤,也不能充分利用历史数据的决策来增加最优求解时间。在传统研究的基础上,建立了服务绩效与资源消耗量之间的关系模型(PR模型),用于评估和过滤初始人口,提出了收益函数和终止条件的设计方法。 。它还提出了将经验数据转化为历史决策并在下一个周期中使用它的方法。实验结果表明,该方法能够保持较高的资源利用率,并满足响应时间的要求。 (C)2016由Elsevier B.V.发布

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