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dc.contributor.authorBecedas, J.
dc.contributor.authorGonzález, D.
dc.contributor.authordel Mar Núñez, María
dc.date.accessioned2021-02-10T12:58:18Z
dc.date.issued2018
dc.date.submitted2021-06-02T10:10:32Z
dc.identifierONIX_20210602_10.5772/intechopen.71423_363
dc.identifierhttps://library.oapen.org/handle/20.500.12657/49249
dc.identifier.urihttps://directory.doabooks.org/handle/20.500.12854/70646
dc.description.abstractConventional Earth Observation Payload Data Ground Segments (PDGS) continuously receive variable requests for data processing and distribution. However, their architecture was conceived to be on the premises of satellite operators and, for instance, has intrinsic limitations to offer variable services. In the current chapter, we introduce cloud computing technology to be considered as an alternative to offer variable services. For that purpose, a cloud infrastructure based on OpenNebula and the PDGS used in the Deimos-2 mission was adapted with the objective of optimizing it using the ENTICE open source middleware. Preliminary results with a realistic satellite recording scenario are presented.
dc.languageEnglish
dc.rightsopen access
dc.subject.otherEarth Observation, distributed systems, cloud computing, ENTICE project, gs4EO
dc.subject.otherthema EDItEUR::R Earth Sciences, Geography, Environment, Planning::RG Geography::RGW Geographical information systems, geodata and remote sensing
dc.titleChapter Optimization of an Earth Observation Data Processing and Distribution System
dc.typechapter
oapen.identifier.doi10.5772/intechopen.71423
oapen.relation.isPublishedBy035ecc65-6737-43cf-a13a-6bdf67ce01f4
dc.relationisFundedByH2020-ICT-2014-1


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