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Research on the resource allocation algorithm based on forecasting in mobile cloud computing

机译:基于移动云计算预测的资源分配算法研究

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摘要

With the construction and application of large-scale datacenters, the issue of resource allocation in cloud computing becomes a serious concern. Although the current static allocation method can make applications get corresponding resources, there still exist some shortcomings such as resource surpluses or shortages. This kind of problem is more crucial in real-time requirements of mobile cloud computing service. Therefore, it is necessary to establish a forecasting model to predict the future resource demands, and then perform on-demand distribution, which can effectively reduce the unnecessary daily network management fees and address the issues mentioned above. This paper focuses on CPU resource forecasting, establishing three forecasting models including Markov chain, weighted Markov chain and stacking weighted Markov chain. By comparing and analyzing the experiment results, the most reasonable forecasting model is found and explained.
机译:随着大规模数据中心的建设和应用,云计算中的资源分配问题成为一个备受关注的问题。虽然目前的静态分配方法可以使应用程序获得相应的资源,但仍然存在资源过剩或短缺等缺点。这种问题在移动云计算服务的实时性需求中更为关键。因此,有必要建立一个预测模型来预测未来的资源需求,然后进行按需分配,这样可以有效地减少不必要的日常网络管理费用,解决上述问题。本文以CPU资源预测为研究对象,建立了马尔可夫链、加权马尔可夫链和叠加加权马尔可夫链三种预测模型。通过对实验结果的比较和分析,找到并解释了最合理的预测模型。

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