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Erschienen in:
2019 | OriginalPaper | Buchkapitel
PDRM: A Probability Distribution Based Resource Management for Batch Workloads in Heterogeneous Cluster
verfasst von : Jun Zhou, Dan Feng, Fang Wang
Erschienen in: Network and Parallel Computing
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Abstract
Resource consumption prediction and dynamic resource provision based on historical consumption are common methods to improve cluster resource utilization, however they have to face the challenge of fluctuation in resource consumption for accurate prediction. We propose PDRM, an efficient resource management scheme based on resource consumption probability distribution for batch workloads to deal with this dilemma. Based on the common sense that the same type of tasks have similar resource consumption on the same node, we get the resource consumption probability distribution of each type of task to describe the fluctuations in its resource consumption. Based on the resource consumption distribution function, we can allocate resources precisely for tasks. Experimental results demonstrate that PDRM achieves good performance for various application in the heterogeneous cluster. PDRM can effectively improve resource utilization and reduce job completion time.