Title :
An intelligent analysis and prediction model for on-demand cloud computing systems
Author :
Xiuju Fu ; Xiaorong Li ; Yongqing Zhu ; Lipo Wang ; Goh, Rick Siow Mong
Author_Institution :
Inst. of High Performance Comput., Singapore, Singapore
Abstract :
In this paper, an intelligent model for analyzing and predicting cloud computing resource utilization is proposed to enhance on-demand services in cloud computing systems. The model is with the capability to discover active users and mine the system storage utilization patterns. This model is also with learning capabilities to adapt the dynamics in the cloud computing platform by capturing changing patterns of system storage utilization, and it employs data mining means for computing the practical model to be used for prediction and providing inputs for intelligent management in the on-demand cloud computing system. We have evaluated the proposed analysis and prediction model in a cloud computing platform. High prediction accuracies of 95% and 86% have been achieved in 1-day ahead and 7-day ahead system utilization prediction, respectively.
Keywords :
cloud computing; data mining; active users; data mining; intelligent management; on-demand cloud computing systems; on-demand services; system storage utilization patterns; Analytical models; Cloud computing; Computational modeling; Data mining; Data models; Planning; Predictive models;
Conference_Titel :
Neural Networks (IJCNN), 2014 International Joint Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4799-6627-1
DOI :
10.1109/IJCNN.2014.6889875