期刊名称：International Journal of Grid and Distributed Computing
印刷版ISSN：2005-4262
出版年度：2014
卷号：7
期号：2
页码：41-52
DOI：10.14257/ijgdc.2014.7.2.05
出版社：SERSC
摘要：In the cloud computing environment, according to the predicting average response time of service, it can adjust to the follow-up system, so that the response time of the system is acceptable. The traditional methods of predicting average response time of serve mainly include the method of gray predicting and neural network model, but the two methods face several problems, such as longer processing time and unsuitable to larger volatility data. According to the above problems, the paper proposes the method of predicting average response time of cloud service based on the MGM (1, N) - BP neural network, the combination of two methods of predicting can use less sample information, it can get a high precision of predicting result and it can also predict the volatile system. Experimental results show the feasibility and effectiveness of the method.
关键词：MGM(1;N)-BP neural network; cloud service; the average response time; the ; predicting method
