A Predictive Method for Workload Forecasting in the Cloud Environment

• Main Authors: Feng-Wei Chuang, 莊峰瑋
• Other Authors: Ruay-Shiung Chang
• Format: Others
• Published: 2013
• Online Access: http://ndltd.ncl.edu.tw/handle/47248265463757800553

碩士 === 國立東華大學 === 資訊工程學系 === 101 === Cloud computing provides powerful computing capabilities, and also provides a flexible user pay mechanism, which makes the cloud more convenient. Due to a steady increase in the amount of data, people are getting more and more use out of the cloud. Therefore, in order to improve the performance and energy savings of the cloud, its resource allocation efficiency has become very important. In this thesis, we propose a neural network model to predict the workload of Cloud servers. Through this prediction mechanism, cloud service providers can know the following time workload of Cloud servers in advance. Thus, the server can avoid the problem of inadequate resources. Resources can be allocated efficiently and become load balanced by the mechanism.