A feedback based prediction model for real time workload in a cloud
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,...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Asian Research Publication Network
2016
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| Online Access: | http://psasir.upm.edu.my/id/eprint/43495/1/A%20feedback%20based%20prediction%20model%20for%20real%20time%20workload%20in%20a%20cloud.pdf http://psasir.upm.edu.my/id/eprint/43495/ |
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| Summary: | 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. |
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