Services Based on the Enriched Profile of a Person Within a Smart University

Delgado, Viky Julieta Arias; González, Enríque

doi:10.1007/978-3-030-68285-9_16

Cited by 1 publication

(1 citation statement)

References 28 publications

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“…Xiao et al [29] proposed a topology-adaptive DCN, which could perform virtual machine migration more effectively. Enzo et al [30] designed an algorithm to reduce the memory energy consumption of a virtual machine and their communication as much as possible according to the quality of service policy at migration time. As compared to random scheduling migration and real-time workflow, this method had better performance in reducing energy consumption and migration time duration.…”

Section: Related Workmentioning

confidence: 99%

Research on energy‐saving virtual machine migration algorithm for green data center

Zhou

2022

IET Control Theory & Appl

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The cloud computing center can dynamically respond to various needs, schedule computing resources, and provide users with convenient IT services. As the demand for cloud computing services continues to increase, the scale of the data center is getting larger and larger, and the problem of high energy consumption of equipment is becoming more and more prominent. Therefore, building a green data center is key to ensuring the development of the technology industry. Virtual machine online migration technology has been widely used in energy consumption management, which plays an important role in the energy‐saving management of large‐scale data centers. Considering the problem of energy consumption in a multi‐data center environment, a cross‐data center virtual machine migration strategy is proposed, EVMA. First, the target data center of the virtual machine migration is determined according to the bandwidth between data centers, and then the overload host and virtual machine selection strategy is determined according to the historical CPU load. The experimental results showed that the algorithm had a good performance in reducing the energy consumption of the data center and ensuring the quality of service.

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Section: Related Workmentioning

confidence: 99%

Research on energy‐saving virtual machine migration algorithm for green data center

Zhou

2022

IET Control Theory & Appl

View full text Add to dashboard Cite

show abstract

Services Based on the Enriched Profile of a Person Within a Smart University

Cited by 1 publication

References 28 publications

Research on energy‐saving virtual machine migration algorithm for green data center

Research on energy‐saving virtual machine migration algorithm for green data center

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