Virtual machine placement based on multi-objective reinforcement learning-Reference-Cited by-同舟云学术

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Virtual machine placement based on multi-objective reinforcement learning

Published:2020-03-06 Issue:8 Volume:50 Page:2370-2383
ISSN:0924-669X
Container-title:Applied Intelligence
language:en
Short-container-title:Appl Intell

Author:

Qin Yao^ORCID,Wang Hua,Yi Shanwen,Li Xiaole,Zhai Linbo

Funder

National Natural Science Foundation of China

Fundamental Research Fund of Shandong University

Key Technology Research and Development Program of Shandong

Natural Science Foundation of Shandong Province

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence

Link

http://link.springer.com/content/pdf/10.1007/s10489-020-01633-3.pdf

Reference39 articles.

1. Make IT Green (2010) Cloud computing and its contribution to climate change. Greenpeace International, p 83

2. Wang J, Gong B, Liu H, Li S (2019) Intelligent scheduling with deep fusion of hardware-software energy-saving principles for greening stochastic nonlinear heterogeneous super-systems. Appl Intell, 1–14

3. El Motaki S, Yahyaouy A, Gualous H, Sabor J (2019) Comparative study between exact and metaheuristic approaches for virtual machine placement process as knapsack problem. J Supercomput, 1–21

4. Shaw R, Howley E, Barrett E (2019) An energy efficient anti-correlated virtual machine placement algorithm using resource usage predictions. Simul Model Pract Theory 93:322–342

5. Xu J, Fortes JAB (2010) Multi-objective virtual machine placement in virtualized data center environments. In: 2010 IEEE/ACM int’l conference on & int’l conference on cyber, physical and social computing (CPSCom) green computing and communications (GreenCom). IEEE, pp 179–188

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3. Energy-efficient virtual machine placement in heterogeneous cloud data centers: a clustering-enhanced multi-objective, multi-reward reinforcement learning approach;Cluster Computing;2024-07-15

4. Enhancing virtual machine placement efficiency in cloud data centers: a hybrid approach using multi-objective reinforcement learning and clustering strategies;Computing;2024-07-02

5. Data transmission optimization in edge computing using multi-objective reinforcement learning;The Journal of Supercomputing;2024-06-06

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