文章基本信息

标题：A FEEDBACK BASED PREDICTION MODEL FOR REAL-TIME WORKLOAD IN A CLOUD
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作者：BABAK ESMAEILPOUR GHOUCHANI ; AZIZOL ABDULLAH ; NOR ASILA WATI ABDUL HAMID 等
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