An optimal disk allocation in cloud virtual machine deployment

Huang, Li-Shing; Chen, Hsin-Hung; Chen, Jianbo; Pao, Tsang-Long

doi:10.1109/icamse.2016.7840199

Cited by 1 publication

(2 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To improve the resource utilization and deploy VMs efficiently, many studies have been done from different aspects and many interesting results have been obtained. [11][12][13][14][15][16][17][18][19][20][21][22] Generally, current studies take VM deployment as the objective optimization problem, and try to solve the problem with heuristics, genetic algorithms, particle swarm algorithms, and so on. And they can be classified into two categories.…”

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Application features‐based virtual machine deployment strategy in cloud environment

Liu

Peng

Zhang

et al. 2021

Concurrency and Computation

View full text Add to dashboard Cite

Traditionally virtual machine (VM) deployment is based on one or two resources on the hosts and rarely considers other resources as well as the resource preferences of different applications. This leads to the imbalance and inefficient utilization of the resources on the physical hosts which further results in the waste of the cloud resources. To solve this problem, a novel VM deployment strategy is proposed. In consideration of the features of applications, the strategy deploys VMs based on the resource preferences of applications as well as the remained resources of the hosts. Utilizing the resource preferences the weights of various resources are determined, and the weight tables for VMs are obtained. Combining the resources weights of VMs and the resource configurations of physical hosts the values whether the resources are used in balance are calculated. To verify the correctness and effectiveness of the proposed strategy, extensive experiments were carried out on Cloudsim. Experimental results show that the proposed strategy is correct and effective. It outperforms other algorithms in VM deployment and ensures that the cloud resources are more efficiently utilized.

show abstract

Section: Related Workmentioning

confidence: 99%

“…The first category tries to study VM deployment as a single objective optimization problem. 3,[15][16][17][18]21,[23][24][25] These studies use energy consumption or QoS or SLA as the target and try to deploy VM on the hosts. For example, Song et al 23 proposed an application-aware scheme for VM placement.…”

Section: Related Workmentioning

confidence: 99%