NDLI: StorkCloud: data transfer scheduling and optimization as a service

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StorkCloud: data transfer scheduling and optimization as a service

Content Provider	ACM Digital Library
Author	Kosar, Tevfik Zhang, Bing Arslan, Engin Ross, Brandon
Abstract	Wide-area transfer of large data sets is still a big challenge despite the deployment of high-bandwidth networks with speeds reaching 100 Gbps. Most users fail to obtain even a fraction of theoretical speeds promised by these networks. Effective usage of the available network capacity has become increasingly important for wide-area data movement. We have developed a "data transfer scheduling and optimization system as a Cloud-hosted service", StorkCloud, which will mitigate the large-scale end-to-end data movement bottleneck by efficiently utilizing underlying networks and effectively scheduling and optimizing data transfers. In this paper, we present the initial design and prototype implementation of StorkCloud, and show its effectiveness in large dataset transfers across geographically distant storage sites, data centers, and collaborating institutions.
Starting Page	29
Ending Page	36
Page Count	8
File Format	PDF
ISBN	9781450319799
DOI	10.1145/2465848.2465855
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2013-06-17
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	End-to-end throughput optimization Cloud computing Software as a service (saas) Big data Data scheduling.
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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