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Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229
ROMANIA

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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  4/2016 - 2

Speeding Up VM Image Distribution for Cloud Data Centers

LEE, C. See more information about LEE, C. on SCOPUS See more information about LEE, C. on IEEExplore See more information about LEE, C. on Web of Science, LEE, H. See more information about  LEE, H. on SCOPUS See more information about  LEE, H. on SCOPUS See more information about LEE, H. on Web of Science, KIM, E. See more information about KIM, E. on SCOPUS See more information about KIM, E. on SCOPUS See more information about KIM, E. on Web of Science
 
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Download PDF pdficon (1,353 KB) | Citation | Downloads: 931 | Views: 2,679

Author keywords
computer networks, content distribution networks, distributed computing, peer-to-peer computing, protocols

References keywords
cloud(15), virtual(9), computing(8), data(7), machine(6), chen(6), systems(5), performance(5), network(5), usenix(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2016-11-30
Volume 16, Issue 4, Year 2016, On page(s): 9 - 14
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2016.04002
Web of Science Accession Number: 000390675900002
SCOPUS ID: 85007597186

Abstract
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Full text preview
An efficient scheme of virtual machine image dissemination, which takes up a major portion of VM provisioning time, is key to ensuring that the service can be provisioned and delivered to clients in a timely manner. This paper presents a novel peer-to-peer protocol to efficiently distribute virtual machine images in a cloud data center. The primary idea of our proposal is to expedite the peer-to-peer content delivery by taking advantage of a high level of similarity that oftentimes exists among different VM images. The efficacy of our protocol is validated through an evaluation that demonstrates substantial performance gains over existing approaches.


References | Cited By  «-- Click to see who has cited this paper

[1] M. Mao and M. Humphrey, "A performance study on the VM startup time in the cloud," in Proc. 5th IEEE International Conference on Cloud Computing (CLOUD), Honolulu, HI, USA, Jun. 2012, pp.423-430.
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[2] W. Xiong and L. Chen, "HiGIS: An open framework for high performance geographic information system," Advances in Electrical and Computer Engineering, vol.15, no.3, pp.123-132, August 2015,
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[CrossRef] [SCOPUS Times Cited 43]


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[14] U. Deshpande, B. Schlinker, E. Adler, and K. Gopalan, "Gang migration of virtual machines using cluster-wide deduplication," in Proc. 13th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, Delft, Netherlands, May 2013, pp.394-401.
[CrossRef] [Web of Science Times Cited 24] [SCOPUS Times Cited 40]


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[CrossRef] [SCOPUS Times Cited 75]


[18] Z. Shen, Z. Zhang, A. Kochut, A. Karve, H. Chen, M. Kimand, and H. Lei, "VMAR: optimizing I/O performance and resource utilization in the cloud," in Proc. 14th ACM/IFIP/USENIX International Middleware Conference, Beijing, China, Dec. 2013.
[CrossRef] [SCOPUS Times Cited 11]


[19] Z. Chen, Y. Zhao, X. Miao, Y. Chen, and Q. Wang, "Rapid provisioning of cloud infrastructure leveraging peer-to-peer networks," in Proc. 29th IEEE International Conference on Distributed Computing Systems (ICDCS) Workshops, Montreal, Canada, Jun. 2009, pp.324-329.
[CrossRef] [SCOPUS Times Cited 39]


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[CrossRef] [SCOPUS Times Cited 13]


[21] B. Nicolae, A. Kochut, and A. Karve, "Discovering and leveraging content similarity to optimize collective on-demand data access to IaaS cloud storage," in Proc. 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, Shenzhen, China, May 2015, pp.211-220.
[CrossRef] [Web of Science Times Cited 5] [SCOPUS Times Cited 8]


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[23] H. Lai, Y. Wu, and Y. Cheng, "Exploiting neighborhood similarity for virtual machine migration over wide-area network," in Proc. 7th IEEE International Conference on Software Security and Reliability, Washington, D.C., USA, Jun. 2013, pp.149-158.
[CrossRef] [Web of Science Times Cited 7] [SCOPUS Times Cited 8]


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References Weight

Web of Science® Citations for all references: 107 TCR
SCOPUS® Citations for all references: 2,153 TCR

Web of Science® Average Citations per reference: 4 ACR
SCOPUS® Average Citations per reference: 83 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2024-04-18 06:41 in 144 seconds.




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Stefan cel Mare University of Suceava, Romania


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