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Investigating the use of autonomic cloudbursts within the MapReduce framework
Descriptive
TitleInfo
Title
Investigating the use of autonomic cloudbursts within the MapReduce framework
Name
(type = personal)
NamePart
(type = family)
Hegde
NamePart
(type = given)
Samprita
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Samprita Hegde
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(authority = RULIB)
author
Name
(type = personal)
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(type = family)
Parashar
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(type = given)
Manish
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Manish Parashar
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Advisory Committee
Role
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chair
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(type = personal)
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(type = family)
Marsic
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(type = given)
Ivan
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Ivan Marsic
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Advisory Committee
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internal member
Name
(type = personal)
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(type = family)
Pompili
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(type = given)
Dario
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Dario Pompili
Affiliation
Advisory Committee
Role
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internal member
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Rutgers University
Role
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(authority = RULIB)
degree grantor
Name
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NamePart
Graduate School - New Brunswick
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school
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Text
Genre
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theses
OriginInfo
DateCreated
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2011
DateOther
(qualifier = exact);
(type = degree)
2011-05
Place
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xx
Language
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(type = code)
eng
Abstract
(type = abstract)
Today MapReduce framework is increasingly becoming a popular programming paradigm for data intensive computing, especially when there is ad-hoc data to be processed. In MapReduce programming paradigm, computation is done in two stages - a map stage and a reduce stage. The users simply have to provide a ‘map’ and a ‘reduce’ function and the underlying framework handles parallelizing and distributing the computation to worker nodes. Currently, the existing MapReduce frameworks work like a batch processing system where the cluster size is assumed to be static. We have developed a new objective-based scheduler which: 1. Provides both deadline and budget based scheduling capability 2. Provides cloudbursting capability where a computation can “burst” out to cloud whenever the existing datacenter is not capable of meeting the objective. Using these features, it is possible to run any MapReduce application subject to a user objective on any existing cluster by leveraging utility cloud resources. In this thesis, we use the Comet coordination engine and the MapReduce framework which is built on top of Comet Engine. The new autonomic scheduler works with the MapReduce Framework and manages the cluster as well as cloud in order to meet computation requirements. We have investigated the use of cloudbursting for MapReduce applications. We found that it is possible to run the application subject to both time and budget based objectives and successfully complete a job by efficiently using datacenter as well as cloud infrastructures.
Subject
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Topic
Electrical and Computer Engineering
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TitleInfo
Title
Rutgers University Electronic Theses and Dissertations
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ETD
Identifier
ETD_3194
PhysicalDescription
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electronic resource
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application/pdf
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text/xml
Extent
vii, 47 p. : ill.
Note
(type = degree)
M.S.
Note
(type = bibliography)
Includes bibliographical references
Note
(type = statement of responsibility)
by Samprita Hegde
Subject
(authority = ETD-LCSH)
Topic
Computer systems
Identifier
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http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000061267
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TitleInfo
Title
Graduate School - New Brunswick Electronic Theses and Dissertations
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rucore19991600001
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NjNbRU
Identifier
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doi:10.7282/T3FF3RQ8
Genre
(authority = ExL-Esploro)
ETD graduate
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Rights
RightsDeclaration
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The author owns the copyright to this work.
RightsHolder
(type = personal)
Name
FamilyName
Hegde
GivenName
Samprita
Role
Copyright Holder
RightsEvent
Type
Permission or license
DateTime
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(qualifier = exact);
(point = start)
2011-03-29 23:18:52
AssociatedEntity
Name
Samprita Hegde
Role
Copyright holder
Affiliation
Rutgers University. Graduate School - New Brunswick
AssociatedObject
Type
License
Name
Author Agreement License
Detail
I hereby grant to the Rutgers University Libraries and to my school the non-exclusive right to archive, reproduce and distribute my thesis or dissertation, in whole or in part, and/or my abstract, in whole or in part, in and from an electronic format, subject to the release date subsequently stipulated in this submittal form and approved by my school. I represent and stipulate that the thesis or dissertation and its abstract are my original work, that they do not infringe or violate any rights of others, and that I make these grants as the sole owner of the rights to my thesis or dissertation and its abstract. I represent that I have obtained written permissions, when necessary, from the owner(s) of each third party copyrighted matter to be included in my thesis or dissertation and will supply copies of such upon request by my school. I acknowledge that RU ETD and my school will not distribute my thesis or dissertation or its abstract if, in their reasonable judgment, they believe all such rights have not been secured. I acknowledge that I retain ownership rights to the copyright of my work. I also retain the right to use all or part of this thesis or dissertation in future works, such as articles or books.
Copyright
Status
Copyright protected
Availability
Status
Open
Reason
Permission or license
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Technical
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