摘要
针对云平台负载预测方法中对CPU、内存利用率等不同类型负载之间的相关性考虑不足且准确度较低的问题,提出一种基于改进云模型的负载预测方法。该预测方法考虑了CPU、内存之间的相关性,通过提出亲密云和重叠云的概念对云概念模型进行跃升,并综合考虑了负载数据的历史特性和当前变化趋势,由此建立基于云模型的负载预测模型。仿真实验表明,基于云模型的预测方法的预测精度高于其他预测模型,是云计算中负载预测的一种有效方法。
To solve the problems that the forecasting models of cloud computing loads take insufficient account of the correlation between different loads and have low accuracy,this paper proposed a load forecasting based on improved cloud model. By presenting the concepts of similar cloud and overlap cloud to obtain the zooming conceptions cloud model,it considered the correlation between CPU and memory and combined the historical features and the current trends. The simulation results show that the forecasting model based on improved cloud model provide more precise of forecasting than the other forecasting models.Thus,the forecasting based on improved cloud model is demonstrated to be efficient for the load forecasting of cloud computing.
出处
《计算机应用研究》
CSCD
北大核心
2015年第10期3124-3127,共4页
Application Research of Computers
关键词
云计算
负载预测
云模型
概念跃升
cloud computing
load forecasting
cloud model
conception zooming
作者简介
刘晓艳（1988-），女，江苏连云港人，硕士研究生，主要研究方向为云计算、资源管理、虚拟机调度等（lxy_yr@163．com）；
王颖（1989-），女，硕士研究生，主要研究方向为资源管理、云计算等．
