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Cluster Computing
Published in: Cluster Computing 4/2018

25-08-2018

Towards operational cost minimization for cloud bursting with deadline constraints in hybrid clouds

Authors: Chunlin Li, Jianhang Tang, Youlong Luo

Published in: Cluster Computing | Issue 4/2018

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Abstract

In hybrid clouds, there is a technique named cloud bursting which can allow companies to expand their capacity to meet the demands of peak workloads in a low-priced manner. In this work, a cost-aware job scheduling approach based on queueing theory in hybrid clouds is proposed. The job scheduling problem in the private cloud is modeled as a queueing model. A genetic algorithm is applied to achieve optimal queues for jobs to improve the utilization rate of the private cloud. Then, the task execution time is predicted by back propagation neural network. The max–min strategy is applied to schedule tasks according to the prediction results in hybrid clouds. Experiments show that our cost-aware job scheduling algorithm can reduce the average job waiting time and average job response time in the private cloud. In additional, our proposed job scheduling algorithm can improve the system throughput of the private cloud. It also can reduce the average task waiting time, average task response time and total costs in hybrid clouds.
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Metadata
Title
Towards operational cost minimization for cloud bursting with deadline constraints in hybrid clouds
Authors
Chunlin Li
Jianhang Tang
Youlong Luo
Publication date
25-08-2018
Publisher
Springer US
Published in
Cluster Computing / Issue 4/2018
Print ISSN: 1386-7857
Electronic ISSN: 1573-7543
DOI
https://doi.org/10.1007/s10586-018-2841-4

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