A survey study on virtual machine migration and server consolidation techniques in DVFS-enabled cloud datacenter: Taxonomy and challenges-Reference-Cited by-同舟云学术

A survey study on virtual machine migration and server consolidation techniques in DVFS-enabled cloud datacenter: Taxonomy and challenges

Published:2020-03 Issue:3 Volume:32 Page:267-286
ISSN:1319-1578
Container-title:Journal of King Saud University - Computer and Information Sciences
language:en
Short-container-title:Journal of King Saud University - Computer and Information Sciences

Author:

Hosseini Shirvani Mirsaeid,Rahmani Amir Masoud^ORCID,Sahafi Amir

Publisher

Elsevier BV

Subject

General Computer Science

Reference126 articles.

1. Rich mobile applications: genesis, taxonomy, and open issues;Abolfazli;J. Netw. Comput. Appl.,2014

2. Virtual machine migration in cloud data centers: a review, taxonomy, and open research issues;Ahmad;J. Supercomput.,2015

3. A survey on virtual machine migration and server consolidation techniques for cloud data centers;Ahmad;J. Netw. Comput. Appl.,2015

4. Server consolidation for heterogeneous computer clusters using Colored Petri Nets and CPN tools;Al-Azzoni;J. King Saud Univ. – Comput. Inform. Sci.,2015

5. The Economics of Cloud Computing: Addressing the Benefits of Infrastructure in the Cloud. White Paper;Alford,2009

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