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  • 标题:A FEEDBACK BASED PREDICTION MODEL FOR REAL-TIME WORKLOAD IN A CLOUD
  • 本地全文:下载
  • 作者:BABAK ESMAEILPOUR GHOUCHANI ; AZIZOL ABDULLAH ; NOR ASILA WATI ABDUL HAMID
  • 期刊名称:Journal of Theoretical and Applied Information Technology
  • 印刷版ISSN:1992-8645
  • 电子版ISSN:1817-3195
  • 出版年度:2016
  • 卷号:87
  • 期号:3
  • 出版社:Journal of Theoretical and Applied
  • 摘要:Most of the distributed systems such as a cloud environment have a nondeterministic structure, and it would cause a serious problem to perform tasks with a time limit. Therefore, many prediction models and performance analyzes being used in the cloud to determine environment for users. Nevertheless, most of these models have a single objective for optimal resource absorption. Which means, they considered just one objective, such as a time limit and other issues are overlooked. In this paper, we proposed a novel model in Cloud to determine environment for the real-time workload. We applied a multi-objective model to absorb optimal resources under reasonable user cost and maximum user sharing. Performance evaluation on CloudSim proves that the new approach outperforms other existing, state-of-the-art methods.
  • 关键词:Cloud Computing; Prediction Model; Time Series; Feedback Based Prediction Model; Resource Provisioning
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