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Document Type

Thesis - University Access Only

Award Date

2013

Degree Name

Master of Science (MS)

Department / School

Electrical Engineering and Computer Science

First Advisor

George Hamer

Abstract

Cloud Computing through various public cloud providers is becoming a more and more effective way for companies and organizations to utilize computing resources. This paper will propose, plan, model, and investigate the feasibility and cost of utilizing cloud computing resources to perform processes on very large sets of binary data. In this case the binary data is the very large Landsat TM and ETM+ sensor archive. Due to the costs of running trials against processing large datasets, a model will be created that can be utilized for predicting cloud performance and cloud costs. This model will be evaluated against real world examples and will be utilized to measure performance of an existing private cloud implementation of a distributed processing system. The determination of this study of the feasibility of the public cloud for this kind of computing will influence what kind of potential future activities could be undertaken by owners of large binary datasets for their processing needs and user based processing demands.

Library of Congress Subject Headings

Cloud computing
Electronic data processing
Natural resources--Remote sensing--Databases
Earth sciences--Remote sensing--Databases.
Geospatial data
Landsat satellites

Description

Includes bibliographical references (pages 74-75).

Format

application/pdf

Number of Pages

83

Publisher

South Dakota State University

Rights

In Copyright - Educational Use Permitted
http://rightsstatements.org/vocab/InC-EDU/1.0/

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