Adaptive resource allocation for preemptable jobs in cloud systems

In cloud computing, computational resources are provided to remote users in the form of leases. For a cloud user, he/she can request multiple cloud services simultaneously. In this case, parallel processing in the cloud system can improve the performance. When applying parallel processing in cloud c...

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Bibliographic Details
Published in2010 10th International Conference on Intelligent Systems Design and Applications pp. 31 - 36
Main Authors Jiayin Li, Meikang Qiu, Jian-Wei Niu, Yu Chen, Zhong Ming
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.11.2010
Subjects
adaptive scheduling
Cloud computing
Computational modeling
Heuristic algorithms
pre-emptable scheduling
Processor scheduling
Resource management
Schedules
Scheduling
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Summary:In cloud computing, computational resources are provided to remote users in the form of leases. For a cloud user, he/she can request multiple cloud services simultaneously. In this case, parallel processing in the cloud system can improve the performance. When applying parallel processing in cloud computing, it is necessary to implement a mechanism to allocate resource and schedule the tasks execution order. Furthermore, a resource allocation mechanism with preemptable task execution can increase the utilization of clouds. In this paper, we propose an adaptive resource allocation algorithm for the cloud system with preemptable tasks. Our algorithms adjust the resource allocation adaptively based on the updated of the actual task executions. And the experimental results show that our algorithms works significantly in the situation where resource contention is fierce.
ISBN:1424481341
9781424481347
ISSN:2164-7143
DOI:10.1109/ISDA.2010.5687294