ACRUM: An adaptive cloud resource utilization model
Jinghe Huo, Shifeng Shang, Zeng Zhang
Abstract
Jinghe Huo, Shifeng Shang, Zeng Zhang
Abstract
Cloud computing provides an elastic, on-demand and high cost-efficient resource allocation model for task executions. Cloud resource provider cloud offers computing resource, typically in the form of virtual machines. During task execution, the load will change from time to time and therefore, it becomes an interesting topic to optimize resource utilization in the cloud computing environment. In this paper, a framework is proposed that can adaptively use cloud resources. After users specify the desired service goal to achieve, the proposed framework then monitors the task execution, and utilizes different pricing models to add or release cloud resources according to the change of cloud resource utilization rate. Experimental result shows that the cost of task execution is reduced greatly.
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Cloud computing provides an elastic, on-demand and high cost-efficient resource allocation model for task executions. Cloud resource provider cloud offers computing resource, typically in the form of virtual machines. During task execution, the load will change from time to time and therefore, it becomes an interesting topic to optimize resource utilization in the cloud computing environment. In this paper, a framework is proposed that can adaptively use cloud resources. After users specify the desired service goal to achieve, the proposed framework then monitors the task execution, and utilizes different pricing models to add or release cloud resources according to the change of cloud resource utilization rate. Experimental result shows that the cost of task execution is reduced greatly.
Key concepts: Cloud computing, Computer science, Virtual machine, Task (project management), Distributed computing, Resource (disambiguation), Resource management (computing), Resource allocation