Public “Cloud” Provisioning for Venus Express VMC Image Processing

doi:10.1007/s42967-019-00014-z

Communications on Applied Mathematics and Computation ›› 2019, Vol. 1 ›› Issue (2): 253-261.doi: 10.1007/s42967-019-00014-z

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Public “Cloud” Provisioning for Venus Express VMC Image Processing

J. L. Vázquez-Poletti¹, M. P. Velasco², S. Jiménez², D. Usero¹, I. M. Llorente¹, L. Vázquez¹, O. Korablev³, D. Belyaev³, M. V. Patsaeva³, I. V. Khatuntsev³

1 Instituto de Matematica Interdisdiciplinar(IMI), Universidad Complutense de Madrid, 28040 Madrid, Spain;
2 Universidad Politécnica de Madrid, 28040 Madrid, Spain;
3 Space Research Institute of Russian Academy of Sciences(IKI), 117997 Moscow, Russia

Received:2018-04-17 Revised:2018-06-03 Online:2019-06-20 Published:2019-06-20
Contact: J. L. Vázquez-Poletti E-mail:jlvazquez@fdi.ucm.es
Supported by:
J.L.Vázquez-Poletti and I.M.Llorente thank the support of the Ministerio de Economía y Competitividad under the project TIN2015-65469-P. M.P. Velasco, S.Jiménez, D.Usero and L. Vázquez thank the partial support of the Ministerio de Economía y Competitividad under the project ESP2016-79135-R. M.P. Velasco and L.Vázquez thank the support of Universidad Complutense de Madrid under the project PR261/16-20246. D.Usero and L.Vázquez thank the support of Instituto de Matemática Interdisciplinar at Universidad Complutense de Madrid.

Abstract

Abstract: In this paper, we consider the implementation of the "cloud" computing strategy to study data sets associated to the atmospheric exploration of the planet Venus. More concretely, the Venus Monitoring Camera (VMC) onboard Venus Express orbiter provided the largest and the longest so far set of ultraviolet (UV), visible and near-IR images for investigation of the atmospheric circulation. To our best knowledge, this is the frst time where the analysis of data from missions to Venus is integrated in the context of the "cloud" computing. The followed path and protocols can be extended to more general cases of space data analysis, and to the general framework of the big data analysis.

Key words: Retrieval, Data integration, Cloud computing, Big data

CLC Number:

J. L. Vázquez-Poletti, M. P. Velasco, S. Jiménez, D. Usero, I. M. Llorente, L. Vázquez, O. Korablev, D. Belyaev, M. V. Patsaeva, I. V. Khatuntsev. Public “Cloud” Provisioning for Venus Express VMC Image Processing[J]. Communications on Applied Mathematics and Computation, 2019, 1(2): 253-261.

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References

1. Armbrust, M., Fox, A., Grifth, R., Joseph, A.D., Katz, R., Konwinski, A., Lee, G., Patterson, D., Rabkin, A., Stoica, I., Zaharia, M.:A view of cloud computing. Commun. ACM 53(4), 50-58(2010). https://doi.org/10.1145/1721654.1721672
2. Kalitkin, N.N.:Chislennye Metody (Numerical Methods). Nauka, Moscow (1978). (in Russian)
3. Khatuntsev, I., Patsaeva, M., Titov, D., Ignatiev, N., Turin, A., Limaye, S., Markiewicz, W., Almeida, M., Roatsch, T., Moissl, R.:Cloud level winds from the Venus Express Monitoring Camera imaging. Icarus 226, 140-158(2013)
4. Montero, R.S., Moreno-Vozmediano, R., Llorente, I.M.:Iaas cloud architecture:from virtualized datacenters to federated cloud infrastructures. Computer 45, 65-72(2012). https://doi.org/10.1109/MC.2012.76
5. Patsaeva, M., Khatuntsev, I., Patsaev, D., Titov, D., Ignatiev, N., Markiewicz, W., Rodin, A.:The relationship between mesoscale circulation and cloud morphology at the upper cloud level of Venus from VMC/Venus express. Planet Sp. Sci. 113-114, 100-108(2015). https://doi.org/10.1016/j.pss.2015.01.013
6. Velasco, M.P., Usero, D., Jiménez, S., Aguirre, C., Vázquez, L.:Mathematics and Mars exploration. Pure. Appl. Geophys. 172, 33-47(2015)
7. Vázquez, L., Jafari, H.:Fractional calculus:theory and numerical methods. Cent. Eur. J. Phys. 11, 1163(2013)
8. Vázquez, L., Valero, F., Romero, P., Martín, M.L., Velasco, M.P., Jiménez, S., Aguirre, C., CaroCarretero, R., Barderas, G., Usero, D., Martínez, G., Llorente, I.M., Vázquez-Poletti, J.L., Pascual, P., Vicente-Retortillo, A., Ramírez-Nicolás, M.:Some elements of the present Martian research environment at Universidad Complutense de Madrid. Bol. Electrón. Soc. Esp. Mat. 14, 3-15(2017)
9. Vázquez, L., Velasco, M.P., Vázquez-Poletti, J.L., Llorente, I.M., Usero, D., Jiménez, S.:Modeling and simulation of the atmospheric dust dynamic:fractional calculus and cloud computing. Int. J. Numer. Anal. Model. 15, 74-85(2018)
10. Vázquez-Poletti, J.L., Santos-Muñoz, D., Llorente, I.M., Valero, F.:A cloud for clouds:weather research and forecasting on a public cloud infrastructure. In:Helfert, M., Desprez, F., Ferguson, D., Leymann, F., Méndez Munoz, V. (eds.) Cloud Computing and Services Sciences. CLOSER 2015. Communications in Computer and Information Science, vol. 512. Springer, Cham (2015)
11. Vázquez-Poletti, J.L., Perhac, J., Ryan, J., Elster, A.C.:Thor:a transparent heterogeneous open resource framework. In:2010 IEEE International Conference On Cluster Computing Workshops and Posters (Cluster Workshops), pp. 1-6(2010). https://doi.org/10.1109/CLUSTERWKSP.2010.5613099

Public “Cloud” Provisioning for Venus Express VMC Image Processing

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