Resource stealing: a resource multiplexing method for mix workloads in cloud system


The cloud computing paradigm enables providing resources on demand. However, most of them focus on a single type of application requiring separate quality of service. In the context that mix heterogeneous workloads are co-scheduled in the cloud, resource multiplexing is the key to improve resource utilization under premise of performance guaranteing. In this paper, we propose a resource stealing mechanism to improve resource multiplexing of cloud resources. It enables free resource fragments reserved by some workloads being utilized by others. To meet certain service level agreement, resource preemption is adopted as a complement to resource stealing. It ensures each workload with a minimum amount of resources when required. Moreover, we propose an adaptive joint resource provisioning algorithm. It integrates our resource multiplexing method into elastic resource provisioning. Experimental results reveal that the proposed algorithms improve resource utilization and workload performance simultaneously.

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This work is supported by project (2013AA01A212) from the National 863 Program of China, project (61202121) from the National Natural Science Foundation of China, Science and technology project (2013Y2-00043) in Guangzhou of China.

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Correspondence to Fuhui Wu.

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Tan, Y., Wu, F., Wu, Q. et al. Resource stealing: a resource multiplexing method for mix workloads in cloud system. J Supercomput 75, 33–49 (2019).

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  • Resource multiplexing
  • Resource stealing
  • Resource preemption
  • Performance guaranteing
  • Mix workloads