Customized compression algorithms for the scientific payload of GAIA

Gaia is the new astrometric mission of the European Space Agency. It will measure the positions and proper motions of more than one billion stars and other objects with unprecedented accuracy, providing a sample of more than 1% of the stellar content of our Galaxy. Such a mission implies large techn...

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Detalles Bibliográficos
Autor: González Villafranca, Alberto
Tipo de recurso: tesis de maestría
Fecha de publicación:2007
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2099.1/5723
Acceso en línea:https://hdl.handle.net/2099.1/5723
Access Level:acceso abierto
Palabra clave:Data compression (Computer science)
Computer algorithms
Gaia
Data compression
Lossless
Customized
Dades Compressió (Informàtica)
Algorismes computacionals
Àrees temàtiques de la UPC::Informàtica::Informàtica teòrica::Algorísmica i teoria de la complexitat
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spelling Customized compression algorithms for the scientific payload of GAIAGonzález Villafranca, AlbertoData compression (Computer science)Computer algorithmsGaiaData compressionLosslessCustomizedDades Compressió (Informàtica)Algorismes computacionalsÀrees temàtiques de la UPC::Informàtica::Informàtica teòrica::Algorísmica i teoria de la complexitatGaia is the new astrometric mission of the European Space Agency. It will measure the positions and proper motions of more than one billion stars and other objects with unprecedented accuracy, providing a sample of more than 1% of the stellar content of our Galaxy. Such a mission implies large technological and design efforts, since it will have to detect, select and measure hundreds of stars every second, sending their data to the Earth – more than 1.5 million kilometers away (1). Thus, the data transmission system must be highly optimized in order to make an efficient use of the downlink. We have focused the master thesis on this aspect; more specifically, we have revised and optimised the existing precompressing algorithms of the different instruments. Also different compression methods are tested in order to increase the final compression ratio. Our main goal is to guarantee the correct transmission of the highest amount of instrument data to the ground station. Therefore, the final ratio is the key factor that shall be analysed here, but CPU consumption and transmission reliability shall be taken into account as wellUniversitat Politècnica de CatalunyaGarcía-Berro Montilla, EnriquePortell de Mora, Jordi20072007-06-2820082008-11-03master thesishttp://purl.org/coar/resource_type/c_bdccNAhttp://purl.org/coar/version/c_be7fb7dd8ff6fe43info:eu-repo/semantics/masterThesisapplication/pdfhttps://hdl.handle.net/2099.1/5723reponame:UPCommons. Portal del coneixement obert de la UPCinstname:Universitat Politècnica de Catalunya (UPC)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2Attribution-NonCommercial-NoDerivs 2.5 Spainhttp://creativecommons.org/licenses/by-nc-nd/2.5/es/info:eu-repo/semantics/openAccessoai:upcommons.upc.edu:2099.1/57232026-05-27T15:37:01Z
dc.title.none.fl_str_mv Customized compression algorithms for the scientific payload of GAIA
title Customized compression algorithms for the scientific payload of GAIA
spellingShingle Customized compression algorithms for the scientific payload of GAIA
González Villafranca, Alberto
Data compression (Computer science)
Computer algorithms
Gaia
Data compression
Lossless
Customized
Dades Compressió (Informàtica)
Algorismes computacionals
Àrees temàtiques de la UPC::Informàtica::Informàtica teòrica::Algorísmica i teoria de la complexitat
title_short Customized compression algorithms for the scientific payload of GAIA
title_full Customized compression algorithms for the scientific payload of GAIA
title_fullStr Customized compression algorithms for the scientific payload of GAIA
title_full_unstemmed Customized compression algorithms for the scientific payload of GAIA
title_sort Customized compression algorithms for the scientific payload of GAIA
dc.creator.none.fl_str_mv González Villafranca, Alberto
author González Villafranca, Alberto
author_facet González Villafranca, Alberto
author_role author
dc.contributor.none.fl_str_mv García-Berro Montilla, Enrique
Portell de Mora, Jordi
dc.subject.none.fl_str_mv Data compression (Computer science)
Computer algorithms
Gaia
Data compression
Lossless
Customized
Dades Compressió (Informàtica)
Algorismes computacionals
Àrees temàtiques de la UPC::Informàtica::Informàtica teòrica::Algorísmica i teoria de la complexitat
topic Data compression (Computer science)
Computer algorithms
Gaia
Data compression
Lossless
Customized
Dades Compressió (Informàtica)
Algorismes computacionals
Àrees temàtiques de la UPC::Informàtica::Informàtica teòrica::Algorísmica i teoria de la complexitat
description Gaia is the new astrometric mission of the European Space Agency. It will measure the positions and proper motions of more than one billion stars and other objects with unprecedented accuracy, providing a sample of more than 1% of the stellar content of our Galaxy. Such a mission implies large technological and design efforts, since it will have to detect, select and measure hundreds of stars every second, sending their data to the Earth – more than 1.5 million kilometers away (1). Thus, the data transmission system must be highly optimized in order to make an efficient use of the downlink. We have focused the master thesis on this aspect; more specifically, we have revised and optimised the existing precompressing algorithms of the different instruments. Also different compression methods are tested in order to increase the final compression ratio. Our main goal is to guarantee the correct transmission of the highest amount of instrument data to the ground station. Therefore, the final ratio is the key factor that shall be analysed here, but CPU consumption and transmission reliability shall be taken into account as well
publishDate 2007
dc.date.none.fl_str_mv 2007
2007-06-28
2008
2008-11-03
dc.type.none.fl_str_mv master thesis
http://purl.org/coar/resource_type/c_bdcc
NA
http://purl.org/coar/version/c_be7fb7dd8ff6fe43
dc.type.openaire.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
dc.identifier.none.fl_str_mv https://hdl.handle.net/2099.1/5723
url https://hdl.handle.net/2099.1/5723
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution-NonCommercial-NoDerivs 2.5 Spain
http://creativecommons.org/licenses/by-nc-nd/2.5/es/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution-NonCommercial-NoDerivs 2.5 Spain
http://creativecommons.org/licenses/by-nc-nd/2.5/es/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universitat Politècnica de Catalunya
publisher.none.fl_str_mv Universitat Politècnica de Catalunya
dc.source.none.fl_str_mv reponame:UPCommons. Portal del coneixement obert de la UPC
instname:Universitat Politècnica de Catalunya (UPC)
instname_str Universitat Politècnica de Catalunya (UPC)
reponame_str UPCommons. Portal del coneixement obert de la UPC
collection UPCommons. Portal del coneixement obert de la UPC
repository.name.fl_str_mv
repository.mail.fl_str_mv
_version_ 1869415092271972352
score 15.301603

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