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Efficient Hybrid Central Processing Unit/ Input-Output Resource Scheduling for Virtual Machines
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DOI：10.1109/TIE.2020.2975466.png)
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摘要
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The use of virtualization technology in industrial control is increasing. However, virtual instances or virtual machines (VMs) are confronted with the unreasonable resource allocation in the industrial control cyber range, thereby highlighting the increasing importance of resource scheduling. In the Xen open source system, the input-output (IO)-intensive task response is extended because the system does not distinguish between CPU- and IO-intensive tasks. Therefore, this article presents an improved task performance through the hybrid scheduling of CPU and network IO resources. This method uses Cap- and Timeslice-scheduling algorithms for CPU resource scheduling. First, the Cap-scheduling algorithm uses historical data to train a recurrent neural network model for classification and then utilizes the heuristic method to set the upper limit of cap value for VMs. Second, the Timeslice-scheduling algorithm adjusts the timeslice based on Q-learning to shorten the execution time of the overall tasks. This article proposes an IOb-scheduling algorithm for network bandwidth scheduling. The part that does not exceed the average bandwidth is eliminated and distributed to other VMs by monitoring the bandwidth usage of each VM, thereby improving the utilization of bandwidth. Experimental results showed that the proposed CPU/IO scheduling algorithms improved the overall benchmark performance substantially.
Keyword:
Task analysis
Job shop scheduling
Bandwidth
Resource management
Optimization
Virtualization
Industrial control
resource scheduling
virtualization
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7.2
论文数:
1.8W
被引数:
9.8W
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Accurate CPU Proportional Share and Predictable I/O Responsiveness for Virtual Machine Monitor: A Case Study in Xen虚拟机监视器的准确CPU比例份额和可预测的I/O响应能力: Xen中的案例研究
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