Chapter Optimization of an Earth Observation Data Processing and Distribution System
| dc.contributor.author | Becedas, J. | |
| dc.contributor.author | González, D. | |
| dc.contributor.author | del Mar Núñez, María | |
| dc.date.accessioned | 2021-06-02T10:10:32Z | |
| dc.date.available | 2021-06-02T10:10:32Z | |
| dc.date.issued | 2018 | |
| dc.identifier | ONIX_20210602_10.5772/intechopen.71423_363 | |
| dc.identifier.uri | https://library.oapen.org/handle/20.500.12657/49249 | |
| dc.description.abstract | Conventional 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.language | English | |
| dc.subject.classification | thema EDItEUR::R Earth Sciences, Geography, Environment, Planning::RG Geography::RGW Geographical information systems, geodata and remote sensing | en_US |
| dc.subject.other | Earth Observation, distributed systems, cloud computing, ENTICE project, gs4EO | |
| dc.title | Chapter Optimization of an Earth Observation Data Processing and Distribution System | |
| dc.type | chapter | |
| oapen.identifier.doi | 10.5772/intechopen.71423 | |
| oapen.relation.isPublishedBy | 09f6769d-48ed-467d-b150-4cf2680656a1 | |
| oapen.relation.isFundedBy | H2020-ICT-2014-1 | |
| oapen.grant.number | 644179 | |
| oapen.grant.acronym | ENTICE |
