Improving Energy Efficiency of Virtual Resource Allocation In Cloud Datacenter

Mahendran, N.; Mekala, T.

doi:10.17485/ijst/2018/v11i19/123227

Cited by 5 publications

(1 citation statement)

References 3 publications

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“…According to the definition, the variation value of the resource utilization rate is equal to the average variance of the resource state vector of the physical server P, which is represented by the symbol p  [24,25]. Calculated as follows:…”

Section: Virtual Resource Allocation Algorithmmentioning

confidence: 99%

Cloud Computing Virtual Resource Dynamic System Allocation and Application Based on System Architecture

Yan¹

2021

DSA

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Cloud computing is a way to build dynamic systems based on sharing, which can connect large system pools to provide services. The purpose of this paper is to study the layout and application of cloud computing virtual resource allocation dynamic system based on system structure, to ensure the load balance of virtual resource mixing and reduce resource waste. By using the cluster network topology, the resource utilization of dynamic system clusters can be monitored in real-time, and the current overall load status of the cluster can be automatically determined according to the monitoring data. The experiment is divided into two parts: performance test and scene test. The performance test mainly tests the operation time, CPU operation and memory operation. The scenario test uses JMeter simulation to generate a large number of simultaneous application access requests, as well as the loss rate and processing reaction time of these requests on the cloud service platform and performs load balancing test. The experimental results show that the running time of the system is about 22 to 27 ms, the CPU utilization is about 90% to 95%, and the average running memory is about 3.5m. The results show that cloud computing technology can improve the resource scheduling efficiency of large-scale tasks and optimize the load distribution of resources.

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Section: Virtual Resource Allocation Algorithmmentioning

confidence: 99%